M Olmedilla

M R Martínez-Torres

S L Toral

The superhit effect and long tail phenomenon in the context of electronic word of mouth

Keywords: Electronic word of mouth (eWOM), user-generated content, long tail, power-law fitting, elbow criterion

The superhit effect and long tail phenomenon in the context of electronic word of mouth

The proliferation of online retailers combined with recommender systems has facilitated the availability of various products and services through the Internet. However, the effect of this availability depends on the products' categories: in some cases, the web promotes the superhit products even more while keeping a short tail; however, in other cases, a long tail effect emerges. This paper investigates the coexistence of the superhit effect and long tail phenomenon from a quantitative perspective and proposes two different methods to mathematically indicate the presence of both phenomena in 28 different product categories collected from an eWOM (electronic word of mouth) website. The aim is to test whether the Internet promotes best-seller products, niche products or both. The findings reveal that eWOM promotes either the long tail phenomenon or superhit effect depending on the different product categories and that they can coexist.

Introduction

The effect of the Internet and the increase in information available to the consumer are redefining a shift in the distribution of the sales of products that are reviewed and purchased online. This subject has gained much attention and discussion among research related to information systems, marketing or operation management [START_REF] Olmedilla | Examining the power-law distribution among eWOM communities: a characterisation approach of the Long Tail[END_REF][29] [START_REF] Brynjolfsson | Consumer surplus in the digital economy: Estimating the value of increased product variety at online booksellers[END_REF]. In this respect, online markets have proposed that nonhit or niche products represent an important part of the overall product sales [START_REF] Gu | The influence of online word-of-mouth on long tail formation[END_REF]. This transformation of the distribution of product sales is what Anderson called the long tail [START_REF] Anderson | The long tail[END_REF]. The long tail phenomenon can be explained because, although consumers can now find everything effortlessly on the Internet, their choices are based on preferences that are not similarly distributed [START_REF] Clemons | How information changes consumer behavior and how consumer behavior determines corporate strategy[END_REF]. Moreover, different search technologies [START_REF] Hinz | Drivers of the long tail phenomenon: an empirical analysis[END_REF] or peer-based recommendations associated with electronic commerce [START_REF] Oestreicher-Singer | Recommendation networks and the long tail of electronic commerce[END_REF] are strongly related to the phenomenon of the long tail of demand because they lead to redistribution of the demand toward niche products and popular products.

Actually, the influence of recommender systems in this point seems to be contradictory because they can promote both niche and popular products. However, this is an open debate in the current literature. In this regard, earlier studies have driven a wedge between two differing directions. On the one hand, research in favor of the long tail idea upholds that boosting the collection of products accessible over online channels (e.g., eWOM communities) will strengthen the sales of niche products [START_REF] Brynjolfsson | Goodbye pareto principle, hello long tail: The effect of search costs on the concentration of product sales[END_REF] [START_REF] Elberse | Should you invest in the long tail?[END_REF]; however, others advocate the sales of popular products with even high ratings [START_REF] Standifird | Reputation and ecommerce: eBay auction and the asymmetrical impact of positive and negative ratings[END_REF]. In both cases, the role of online channels is the same: to help consumers find their desired product, regardless of whether they are less popular or superhit products. The only difference is that, in some cases, the tail is extended, while in others, the tail is shortened [START_REF] Lee | The long tail or the short tail: The category-specific impact of eWOM on sales distribution[END_REF].

Many existing studies on the topic focus on e-commerce sites [START_REF] Brynjolfsson | Consumer surplus in the digital economy: Estimating the value of increased product variety at online booksellers[END_REF][9] [START_REF] Brynjolfsson | Goodbye pareto principle, hello long tail: The effect of search costs on the concentration of product sales[END_REF], Web search distributions [START_REF] Huberman | Bootstrapping the long tail in peer to peer systems[END_REF] or cultural products such as music [START_REF] Elberse | Should you invest in the long tail?[END_REF], books, films or video games [START_REF] Tucker | How does popularity information affect choices? A field experiment[END_REF].

This paper expands the border of the long tail quantitative research by providing a new perspective on the understanding of both the superhit effect and long tail phenomenon of consumption patterns of online users within an eWOM community. Specifically, the presence of superhit or niche products is studied across the entire spectrum of product categories distributed within an eWOM community. This analysis is based on a unique data set of 105,918 online reviews of 68,650 products posted on a popular eWOM community by [START_REF] Liu | Word of mouth for movies: Its dynamics and impact on box office revenue[END_REF]352 different users. The accessibility to online reviews posted by users within the proper product category and subcategory allows differentiating the type of distribution across products.

The overall aim of the paper was to test whether the existence of the superhit effect is compatible with the long tail phenomenon. To that end, this study compares two methodologies to mathematically measure a heavy-tailed and a long tail distribution: the power-law fitting method of the distribution of the number of products (supply side factor) per number of online reviews (demand side factor), previously proposed by Clauset et al. [START_REF] Clauset | Power-law distributions in empirical data[END_REF] and developed by Olmedilla et al. [START_REF] Olmedilla | Examining the power-law distribution among eWOM communities: a characterisation approach of the Long Tail[END_REF], as well as the elbow criterion demarcated by the power-law fitting. The main contribution of the proposed methodology is its ability to mathematically determine the presence of superhit and niche products.

The remainder of the paper is organized as follows. The next section discusses the related work and conceptual framework by conducting a literature review to develop the two proposed research questions. The section thereafter describes the research methodology.

Here, the case study and data collection are detailed as well as the two methods used to fit the power-law distribution. The results are next presented. Finally, the study concludes with the discussion and implications of the study.

Related work and conceptual framework

Superhit effect vs long tail phenomenon

As aforementioned, the power-law distribution curve presents a small group of highfrequency events at the head followed by a large set of low-frequency events in the tail. In the sales distribution, which acquires the form of a power-law distribution, the head represents the superhit products and the long tail the niche products [START_REF] Koçaş | A system for pricing the sales distribution from blockbusters to the long tail[END_REF]. Figure 1 depicts an example of a power-law distribution with all probable events ranked by their frequency. To the left (blue) are the superhits that dominate and to the right (orange) is the long tail with the niche content.

In this example, there is a red cutoff selected so that areas of both the head and long tail are equal. Actually, according to Elberse [START_REF] Elberse | Should you invest in the long tail?[END_REF], the orange area under the curve may become larger than the blue area over time.

[ FIGURE 1] The superhit effect and long tail phenomenon are two contrasted theories still studied among many researchers. The long tail theory advocates that a big part of consumers prefer popular content while only a minority pursue the niche content [START_REF] Goel | Anatomy of the long tail: ordinary people with extraordinary tastes[END_REF]. In this regard, Anderson [START_REF] Anderson | The long tail[END_REF] theorizes that the tail at the end of the distribution curve is practically different from the head. He adds that consumers are moving toward the niches in the tail since the tail satisfies rare interests better [START_REF] Anderson | Long Tail: Why the Future of Business is Selling Less of More[END_REF]. Today, the Internet is allowing consumers to obtain information related to low-volume products from a massive, geographically dispersed group of people, facilitating this long tail effect [START_REF] Hinz | Drivers of the long tail phenomenon: an empirical analysis[END_REF] [START_REF] Olmedilla | Examining the power-law distribution among eWOM communities: a characterisation approach of the Long Tail[END_REF]. Additionally, in some areas such as music, movies or blogging, the tail is theoretically unlimited because the Internet offers infinite storing space.

Since Anderson [START_REF] Anderson | The long tail[END_REF], the studies presented until now about the long tail have provided a theoretical framework or empirical details about the sales of rare products not available in traditional brick-and-mortar stores. For example, some studies by Brynjolfsson et al. [8][9][10] draw attention to the Internet's long tail by analyzing data collected from a clothing retailer or from sales distributions in product markets such as Amazon. They consider that consumers find it easier to search for and discover niche products because (1) the Internet has eliminated communication barriers as well as stocking and distribution costs; and (2) due to the proliferation of Internet discovery tools such as recommendation engines. Similarly, the author Elberse [START_REF] Elberse | Should you invest in the long tail?[END_REF] argues that the long tail of the sales distribution is becoming longer and fatter using data from Quickflix or Rhapsody Music.

Other researchers studying power-law distributions of the consumers' actions on the Internet find that much of the action occurring within power laws is placed at the head of the distribution where there are fewer events, but with high frequency [START_REF] Dellarocas | long tails: Do consumer reviews increase the informational inequality between hit and niche products?[END_REF], in essence, the superhit effect. This effect was originally presented to describe the few top performers reaching most of the audience and achieving most of the profits [START_REF] Rosen | The economics of superstars[END_REF] and currently still thriving among online markets [START_REF] Brynjolfsson | Research commentary-long tails vs. superstars: The effect of information technology on product variety and sales concentration patterns[END_REF] [START_REF] Zhou | Online user reviews, product variety, and the long tail: An empirical investigation on online software downloads[END_REF]. In this regard, Hennig-Thurau & Houston [START_REF] Hennig-Thurau | Integrated Entertainment Marketing: Creating Blockbusters and Niche Products by Combining Product, Communication, Distribution, and Pricing Decisions[END_REF] provide empirical evidence that the superhit effect still leads in entertainment and guides consumers away from traditional forms of entertainment to new ones such as social media.

Dellarocas [START_REF] Dellarocas | long tails: Do consumer reviews increase the informational inequality between hit and niche products?[END_REF] reveals through Gini coefficient analysis-a measure of the concentration of demand-that the weekly volume of movie online reviews is more skewed toward popular movies. Consequently, thanks to the Internet and digital technologies and networks [START_REF] Brynjolfsson | New world order: labor, capital, and ideas in the power law economy[END_REF], a product becomes more appreciated as the number of users increases, indicating that the superhit effect is affecting more products than before.

Electronic word of mouth (eWOM)

Consumers are progressively participating more in sharing their experiences with a product by writing online reviews, and eWOM is widely recognized as an influential information source on consumer decision making, which is well established in the academic literature [START_REF] Jiménez | Too popular to ignore: The influence of online reviews on purchase intentions of search and experience products[END_REF] [START_REF] Park | The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement[END_REF]. Additionally, the emergence and impact of user-generated content within the Web have made classic WOM move toward eWOM [START_REF] Hennig-Thurau | Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet?[END_REF], which has been enabled by the Internet and online communication [START_REF] Moe | The value of social dynamics in online product ratings forums[END_REF]. Actually, eWOM-considered an inexpensive online medium-is currently decreasing the barriers of entrance into the product markets [START_REF] Martínez-Torres | Analysis of open innovation communities from the perspective of Social Network Analysis[END_REF]. eWOM often has a strong impact on product judgements because the information received is more accessible. Reviews are published on many products and services and have become a part of the decision-making process for consumers [START_REF] Mudambi | What makes a helpful online review? A study of customer reviews on Amazon.com[END_REF].

Evidence from research suggests the capability of eWOM to find niche products, thus facilitating the long tail phenomenon [START_REF] Hennig-Thurau | Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet?[END_REF][37] and the way eWOM is decreasing the cost of the information search about products [START_REF] Odić | Predicting and detecting the relevant contextual information in a movie-recommender system[END_REF]. For example, a study on this topic has concentrated on assessing the relationship between long tail and product sales [START_REF] Brynjolfsson | Research commentary-long tails vs. superstars: The effect of information technology on product variety and sales concentration patterns[END_REF].

Additionally, a more discerning approach is that "the effect of eWOM is not monolithic", but it differs according to product characteristics [START_REF] Manes | The role of electronic word of mouth in reducing information asymmetry: An empirical investigation of online hotel booking[END_REF]. Existing studies on eWOM have primarily dealt with information on products such as movies [START_REF] Yang | Study of Comments on Official Movie Blogs[END_REF][68], books [START_REF] Brynjolfsson | Consumer surplus in the digital economy: Estimating the value of increased product variety at online booksellers[END_REF][15] and music [START_REF] Morales-Arroyo | Identification of critical eWOM dimensions for music albums[END_REF]. In this regard, online reviews within eWOMs are very significant when consumers are choosing products that they do not have first-hand experience with. Online reviews are also generally used to reduce uncertainty regarding service quality from the consumer perspective [START_REF] Reimer | When good WOM hurts and bad WOM gains: The effect of untrustworthy online reviews[END_REF].

Additionally, the study by Park and Lee [START_REF] Park | Information direction, website reputation and eWOM effect: A moderating role of product type[END_REF] describes how eWOM information's direction and website's reputation contribute to the eWOM effect, focusing on the moderating role of the product type.

Fitting power-law distributions online

Not always do the measured processes reach their maximum point around a typical value; sometimes, they diverge across a wide range [START_REF] Newman | Power laws, Pareto distributions and Zipf's law[END_REF]. For example, when the variance and/or mean is no longer finite, the Central Limit Theorem does not predict Gaussian distributions but predicts distributions that resemble power laws. Additionally, unlike normal distributions, observations in power-law distributions are far to the left of the mean and some outliers represent an uneven quantity of the total distribution's output [START_REF] Crawford | Power law distributions in entrepreneurship: Implications for theory and research[END_REF]. In summary, large events occur more often in systems that exhibit power-law distributions. This means that the events in the tail of the distribution are more likely to occur in a power-law distribution, explaining why power laws are also called heavy tailed [3][6]. Thus, the extreme tails are important because they provide an idea of how often, on average, the largest events might occur.

Consequently, power-law distribution is considered a valuable tool to measure these information uncertainties because Gaussian distributions cannot handle them at a certain probability.

Former and current research has examined whether Internet phenomena are better described by power-law distributions [START_REF] Baraba Śi | Emergence of scaling in random networks[END_REF][7] [43][46]. The findings in related fields show that power-law distributions usually emerge in Internet social systems [START_REF] Huberman | The laws of the Web: Patterns in the ecology of information[END_REF], where users express their preferences among many choices (e.g., YouTube [START_REF] Gill | Youtube traffic characterization: a view from the edge[END_REF], eWOM communities [START_REF] Olmedilla | Examining the power-law distribution among eWOM communities: a characterisation approach of the Long Tail[END_REF], and Amazon [START_REF] Chevalier | Measuring prices and price competition online: Amazon.com and BarnesandNoble.com[END_REF]). Similarly, Brynjolfsson, Hu and Smith [START_REF] Brynjolfsson | Consumer surplus in the digital economy: Estimating the value of increased product variety at online booksellers[END_REF] argue that a power-law distribution can be used to describe the relationship between a product's sales rank and sales quantity.

They observed that the interaction of online users exchanging information produces complex dynamics in the demand for products. Consequently, although other heavy-tailed distributions exist (e.g., lognormal, t-distribution, exponential or chi-squared distribution), this paper focuses on the power-law distribution because the superhit effect and long tail phenomenon prevail in online consumption patterns in which a relatively small number of very popular products account for most of the sales [START_REF] Brynjolfsson | Research commentary-long tails vs. superstars: The effect of information technology on product variety and sales concentration patterns[END_REF] and the tail of the distribution encloses niche products [START_REF] Anderson | Long Tail: Why the Future of Business is Selling Less of More[END_REF].

To fit the power-law distribution within this paper the number of reviews is used, not the content. Research has shown that the message content of the online reviews has less impact when users look at many reviews if they are about to make a purchase decision [START_REF] Berger | Positive effects of negative publicity: When negative reviews increase sales[END_REF]. In this regard, Shao [START_REF] Shao | The effects of controversial reviews on product sales performance: The mediating role of the volume of word of mouth[END_REF] argues that a higher number of reviews, either positive or negative, is more probable to gather consumers looking for information and consequently increases product awareness. The author [START_REF] Liu | Word of mouth for movies: Its dynamics and impact on box office revenue[END_REF] defended no relationship between the valence of the online review (negative or positive value assigned to an online review) and sales. In this regard, many authors defended that a higher number has a greater influence on sales [START_REF] Chen | The impact of online recommandations and consumer feedback on sales[END_REF] [44] [START_REF] Duan | Do online reviews matter?-An empirical investigation of panel data[END_REF]. Interestingly, however, review volume does not necessarily mean the reviews are positive. Numerous studies have analyzed the effect of online reviews on product sales or consumers' choices by also considering the characteristics of the reviews. In this respect, Chen et al. [START_REF] Chen | Online social interactions: A natural experiment on word of mouth versus observational learning[END_REF] argued that "negative WOM information has a greater impact on product sales than positive WOM information". In fact, many authors have found that the negative reviews have a better impact on purchase intention than positive reviews [START_REF] Cui | The effect of online consumer reviews on new product sales[END_REF]. This positive effect of negative reviews has been evidenced in numerous studies. For example, Ghose and Ipeirotis [START_REF] Ghose | Estimating the helpfulness and economic impact of product reviews: Mining text and reviewer characteristics[END_REF] associate reviews of products rated negatively with product sales. This author's results are consistent with Berger et al. [START_REF] Berger | Positive effects of negative publicity: When negative reviews increase sales[END_REF] who show that negative reviews have a positive impact on sales because they can increase publicity for lesser known products. Likewise, the results by Gavilan et al. [START_REF] Gavilan | The influence of online ratings and reviews on hotel booking consideration[END_REF] indicate that the negative reviews are used more for holiday decision making than positive ones. In general, users consider negative reviews more useful [START_REF] Sen | Why are you telling me this? An examination into negative consumer reviews on the web[END_REF] or demonstrative for decision-making purposes [START_REF] Lee | The effect of negative online consumer reviews on product attitude: An information processing view[END_REF] than positive reviews, because negative information is attention catching and incites curiosity [START_REF] Ren | Online review systems: How emotional language drives sales[END_REF] and controversial reviews can provoke substantial discussion [START_REF] Shao | The effects of controversial reviews on product sales performance: The mediating role of the volume of word of mouth[END_REF]. Consequently, as the proportion of negative or positive online consumer reviews increases, this indicates that there is a high involvement of consumers. Moreover, the research by Zhang et al. [START_REF] Zhang | Examining the influence of online reviews on consumers' decision-making: A heuristic-systematic model[END_REF] found that consumers who noticed a high number of reviews demonstrated increased arousal of their purchase intention of a product. Additionally, the authors do not explicitly distinguish the number of reviews as positive or negative. Consequently, the more online product reviews that are available, the more likely a consumer will be informed about a product. There are other several relevant articles that have verified a positive impact of online reviews on sales by considering the volume of reviews. For example, a recent article by Maslowska et al. [START_REF] Maslowska | Do customer reviews drive purchase decisions? The moderating roles of review exposure and price[END_REF] found that products that have a high price benefit from a large number of reviews because potential customers detect that others might have bought the product. In this sense, Park et al. [START_REF] Park | The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement[END_REF] also affirmed that the number of reviews can specify a product's popularity due to costumers assuming a relationship between the number of reviews and consumers who have bought the product.

Likewise, the findings by Zhou and Duan [START_REF] Zhou | An empirical study of how third-party websites influence the feedback mechanism between online word-of-mouth and retail sales[END_REF] illustrate that a larger volume of internal WOM, which depends on the number of reviewers, has a positive impact on sales. Extant studies, such as that by Chevalier and Mayzlin [START_REF] Chevalier | The effect of word of mouth on sales: Online book reviews[END_REF], indicate that book sales between two sites (Amazon.com and Barnesandnoble.com) are related to the difference in the number of reviews per book throughout the sites. Additionally, Zhang et al. [START_REF] Zhang | The impact of online user reviews on cameras sales[END_REF] found that the quantity of online reviews, among other characteristics, has an important influence on the sales of digital cameras and search goods.

Research motivation and research questions

Previous research has found that the impact of the Internet on the consumer product discovery process and found differing evidence regarding the shift in the sales distribution for different products. For example, Dellarocas et al. [START_REF] Dellarocas | Are consumers more likely to contribute online reviews for hit or niche products?[END_REF], has studied numerous motivations for consumers to contribute by word of mouth for hit or niche products.

On the one hand, the authors Gu et al. [START_REF] Gu | The influence of online word-of-mouth on long tail formation[END_REF] examined the long tail phenomenon through the informative effect in the context of eWOM. They demonstrated that positive reviews in Amazon enhance the sales of popular products, whereas negative reviews worsen the sales of niche products. Therefore, their results suggest that "online WOM restrains the formation of the long tail". On the other hand, and also using data from Amazon, the study by Chevalier and Mayzlin [START_REF] Chevalier | The effect of word of mouth on sales: Online book reviews[END_REF] found the opposite; online reviews influence book sales. The authors conclude that online review features influence the increase in the number of books sold at Amazon. This argument is also consistent with Zhu and Zhang [START_REF] Zhu | Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics[END_REF], who also advocated that online reviews influence the diffusion and adoption of products that are less popular. Additionally, Hervas-Draney [START_REF] Hervas-Draney | Word of mouth and taste matching: A theory of the long tail[END_REF] showed that WOM benefits more popular products and mainstream consumers and the authors Duan et al. [START_REF] Duan | Do online reviews matter?-An empirical investigation of panel data[END_REF] found that the number of online reviews is significantly associated with movie sales. Thus, the first research question addresses whether online WOM promote either the superhit effect or long tail phenomenon.

RQ1: Does eWOM promote either the superhit effect or long tail phenomenon across product categories?

Furthermore, a large body of literature has studied different evidence sources regarding how the Internet affecting differently the current distribution of products. It has concentrated on assessing the relationship between long tail and product sales [START_REF] Hennig-Thurau | Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet?[END_REF] [START_REF] Brynjolfsson | Research commentary-long tails vs. superstars: The effect of information technology on product variety and sales concentration patterns[END_REF]. For example, researchers have advocated that eWOM is a facilitator of the long tail phenomenon to help identify niche products [START_REF] Dellarocas | long tails: Do consumer reviews increase the informational inequality between hit and niche products?[END_REF]. By contrast, some researchers describe the distribution of products as very unequal with a few extreme outliers accumulated in the head [START_REF] Standifird | Reputation and ecommerce: eBay auction and the asymmetrical impact of positive and negative ratings[END_REF]. Both phenomena are widely acknowledged in the article by Elberse and Oberholzer-Gee [START_REF] Elberse | Superstars and underdogs: An examination of the long tail phenomenon in video sales[END_REF],

where the authors not only found evidence of the long tail effect in home video sales but also found evidence of the superhit effect. This effect was more pronounced among best-selling video titles, which accounted for most of the sales.

An attractive distribution for data generated by these types of cumulative processes is the power law. In this regard, Newman [START_REF] Newman | Power laws, Pareto distributions and Zipf's law[END_REF] provides evidence that book sales do indeed follow a power law. However, little work has focused on whether the power-law distribution is a plausible fit to a data set of different product assortment concentrations. Thus, it would be convenient to model the distribution of product categories with the power law to discern whether there are high-frequency events in the short head or low but larger events in the tail. Thus, the outline arose from this framework encompassing the following research question: RQ2: Is it possible that the superhit effect coexists with the long tail phenomenon?

Research Methodology

Case study and data collection

The eWOM community chosen for data gathering and analysis was Ciao UK, which is a popular website that more than 1.3 million users who have written more than 7 million reviews approximately 1.4 million of products [START_REF] Olmedilla | Examining the power-law distribution among eWOM communities: a characterisation approach of the Long Tail[END_REF]. It has branches in local language in major Western European countries. Three principal sections constitute the eWOM community of Ciao UK: the review section, shopping section and "My Ciao" section, which assess the relevant information about each registered user. Primarily, 28 main product categories have been established by Ciao, and each main category is subdivided into many more subcategories. Thus, registered users post and share their reviews within a specific category and subcategory related to the topic of the review. Almost all main categories have four levels of subcategories. For example, Figure 2 shows the four levels of subcategories for the main category "Travel". In this case, the subcategory level 2 groups the reviews by continent, level 3 by country and level 4 by city. Because level 4 has a sufficient level of detail for travel destination offers, it was selected as the target level in the case of the Travel main category.

[ FIGURE 2] In the case of the main category "Beauty", Figure 3 shows that level 4 has also been selected for data analysis. Although there are further levels of detail, the level of specification given by level 5 is too much (almost indicating the product name) and with very few reviews per subcategory. Thus, level 4 was chosen because the information enclosed is sufficient to study the data and there are many reviews per subcategory within this level.

[ FIGURE 3] Users can access Ciao for free and they also have the option to register. Whether they register, they must create an account where they provide nonmandatory information about themselves (e.g., name, gender, age, and country). To write a review of at least 120 words long, the users have to complete some fields such as the title of the review, name of the product to be reviewed, body containing the user's opinion and advantages and disadvantages. Finally, users post the review within the proper category and subcategory. This is actually the target data that were collected within this paper. Accordingly, the website was completely crawled by extracting a subset of almost 45,000 users, approximately 106,000 reviews of approximately 69,000 products and approximately 283,000 subcategories.

The crawler developed in Olmedilla et al. [START_REF] Olmedilla | Harvesting Big Data in social science: A methodological approach for collecting online user-generated content[END_REF] has been applied to gather the data.

More specifically, the programming language Python has been used to crawl the web combined with an open source web crawler framework called Scrapy. To begin with the scraping cycle of all the categories, an item "review" was defined that contains the fields "main category" and "subcategory" to be collected. Next, to crawl the information of each category, a class named spider was programmed. The spider browses the product webpage and, by using XPath selectors to perform data extractions from the HTML source, all the information about the main categories and subcategories was extracted. To this end, the method response.xpath('text_to_gather').extract() was called and a list with all the elements (vector) of categories was built. Next, the acquired information was stored in the fields "main category" and "subcategory" from the table "product" inside a relational database designed in MySQL. Applying the SQL querying language can be used to access and track all the data stored in the database.

Quantitative techniques

Fitting the power law to gathered data

The first method-the power-law distribution-used by Olmedilla et al. [START_REF] Olmedilla | Examining the power-law distribution among eWOM communities: a characterisation approach of the Long Tail[END_REF] has been extended to decide whether the data set follows a power-law distribution. According to Clauset et al. [START_REF] Clauset | Power-law distributions in empirical data[END_REF], many of the things that scientists measure have a typical size or 'scale'-a typical value around which individual measurements are centered. Hence, a Gaussian distribution occurs. Nevertheless, not all things measured are Gaussian; otherwise, large events are extremely rare within Gaussian distributions. Additionally, those events in the part of the distribution that is far away from the mean and characterized by large and infrequent events-the tail-are more likely to occur in a power-law distribution [START_REF] Clauset | Power-law distributions in empirical data[END_REF]. Consequently, when the probability of peaking around a typical value of some quantity varies over a large dynamic range, these quantities might be consistent with a power-law distribution [START_REF] Newman | Power laws, Pareto distributions and Zipf's law[END_REF], which is defined as:

= ∝ for > (1)
where is the probability (frequency) that the variable takes the value ; ∝ is the exponent of the distribution; the variable to be analyzed; is a constant that depends on the type of event; and is the minimum value of over which the power-law behavior starts.

Because power laws typically describe systems where the larger events are fewer than smaller events, remains positive. This confirms that the power law is a monotonically decreasing function.

Taking logarithms on both sides of (1), it is observed that, for a power-law,

= -∝ , (2)
indicating that, in a graph with logarithmic scale, the relationship between and is described by a straight line whose negative slope is ∝.

In practice, identifying power-law behavior is difficult. In many cases, it is convenient to use the complementary cumulative distribution function (CDF) of a power-lawdistributed variable, which is denoted as

= = ∝ (3)
Essentially, because of applying this power-law distribution method, the cut-off value is obtained. This value defines the point where the power-law distribution is no longer valid. Thus, it is the point beyond which there are no superhit products; consequently, the tail of the distribution starts.

R programming language was used to assess the presence of a power law in the data using the library poweRlaw, which follows the protocol for fitting a power-law model as described by Clauset et al. [START_REF] Clauset | Power-law distributions in empirical data[END_REF]. The function PLFIT was used to estimate and according to the goodness of fit.

Finding the optimal !" based on the elbow criterion

The second method used is based on the elbow criterion, which is an alternative method to determine the cut-off value . According to Kodinariya and Makwana [START_REF] Kodinariya | Review on determining number of Cluster in K-Means Clustering[END_REF], the elbow criterion is a visual method to determine the number of clusters that should be chosen for k-means clustering. This method is based on the relationship between the percentage of variance with respect to the number of clusters to find the optimal number of clusters. In this relationship, plotted as a graph, it was observed that the first positions reveal a high slope because having a low number of clusters may lead to a high percentage of variance between them. If the number of clusters continues to increase to a certain point, the slope decreases. This is because the increase in the number of clusters might not increase the variance as before, indicating that the optimal number of clusters has been exceeded for k-means clustering, producing an angle in the graph [40][45]. Extending the elbow criterion to the case of a power-law distribution, the problem consists of finding the point , where the sharp "elbow" is clearly visible in the graph.

[FIGURE 4]

Figure 4 illustrates the selection of the elbow criterion based on choosing the value with a sharp decrease in the slope of the tangent. Given the function # = ∝ , the tangent line at the point $ % , # % ' is the unique straight line that passes through that point and has the same slope as the graph at that point, which is defined by the derivative value #′ % :

#′ % = )* → , - -, , , (4)
The blue lines of Figure 4 represent the initial and final tangents, corresponding to the slope values of -∞ and 0. The intermediate blue dotted lines represent all the possible intermediate values of the slope. The is the point of the average slope between the two asymptotes of the graph, given by the value -1, which is the point from which the curve goes from decreasing very fast to decreasing very slow.

Results

Following the proposed methodology, a power-law distribution was fitted to the curve of the distribution of subcategories created by the users who have posted reviews over the 28 main categories distinguished by Ciao. The gathered result is shown in Figure 5, which illustrates the distribution of the reviews over the main categories.

[FIGURE 5]

All the distributions obtained show some subcategories are very popular while others are only supported by a few reviews. By applying the two methods described in the previous section, we aimed to determine the presence of the superhit effect and length of the queue for each of the 28 main categories of Ciao.

Table 1 describes in detail the long tail parameters of the 28 main categories according to the power-law adjustment. The first and second column show the and ∝ values of the fitted power-law distribution, respectively. The third column corresponds to the goodness of fit, the p-value. The fourth column shows the length of the tail. The length of the tail has been calculated as the number of subcategories with several reviews below the threshold-that is, the number of subcategories that are not part of the fitted power-law distribution. The fifth and sixth columns represent the areas of the head and tail of the distribution, respectively, calculated also using the value.

The values of distinguish between those subcategories that are part of the head of the power-law distribution (superhit products, above ) and those that belong to the tail (niche products, below ). The ∝ exponent determines the shape of the power-law distribution. The fitting has an associated p-value; thus, in those cases where the calculated p-value is considerably lower than 0.05, the null hypothesis is rejected, indicating that the category does not follow a power-law distribution and there is no superhit effect. However, if the resulting p-value is greater than 0.05, the null hypothesis cannot be rejected; hence, the distribution is likely to follow a power-law distribution and shows a superhit effect. Finally, the head area percentage column denotes the area contained to the left of the cut-off point of , which includes the dominating products or best sellers. The tail area percentage column embodies the tail-that is, the region to the right of the cut-off point of .

[TABLE 1]

The same analysis was conducted but using the elbow method. Table 2 describes the results for the same 28 main categories. The first column displays the values, which correspond to the turning point-that is, the point from which the function goes from decreasing very fast to decreasing very slowly. Accordingly, the function is traversed from the right to the left, from / to -1, until the first point/value that meets the search condition. This is the point of the average slope between the two asymptotes of the graph. The second column shows the length of the tail that was calculated using the calculated turning point.

Finally, the third and fourth columns represent the areas of the head and tail of the distribution, respectively (calculated using the obtained turning point).

[ TABLE 2] Both methods, the power-law fitting method and elbow criterion, were compared in Table 3 to test their coincidence when identifying the presence of the long tail and considering the area and length criteria. The result of this comparison is shown in the last column of Table 3. A True value means that both methods agree concerning the presence or absence of the long tail, a False value means that both methods disagree, and Uncertain means that both methods generate contradictory results. This is the case of Ciao Café, Electronics, Shopping, or Travel. The decision making was conducted by applying the jointratio 80:20 to the area under the tail and length of the tail. An area or length of the tail that is less than 20% of the maximum value indicates the absence of a long tail. Otherwise, the presence of the long tail is accepted.

[TABLE 3] Figure 6 and Figure 7 depict some of the distributions for the main categories shown in Table 3. The graphs show a power-law distribution fitted to the curve of the distribution of subcategories of products. Accordingly, the Y axis corresponds to the volume of reviews (number of reviews written by the users) and the X axis represents all the subcategories of products of each of the 28 main categories of products distinguished by Ciao UK. In both Figure 6 and Figure 7, the value is demarcated by a horizontal red line representing its value calculated by the elbow method, and by a horizontal blue line representing its value calculated by the power-law method. According to Sports & Outdoors, Telecommunications) do not obey a power-law distribution (see Figure 7). Their p-values are small enough so that the power-law model can be firmly discarded, according to their goodness of fit. As a difference and according to their p-values, the remaining 21 categories might be consistent with a power-law distribution. Consequently, and answering RQ1, eWOM promotes both the superhit and long tail phenomena, although the superhit effect is more frequent across the 28 categories considered.

Among all 21 cases with the superhit effect, there are 6 cases without a long tail . These findings answer RQ2 by showing that it is possible that the superhit effect coexists with the long tail phenomenon depending on the product categories.

[FIGURE 6]

[FIGURE 7]
6 Discussion and implications

Theoretical implications

Theoretically, this paper contributes to the growing research on how the Internet influences the superhit effect and formation of the long tail across Internet data and, more specifically, user-generated content. The results suggest that it is important to consider the impact of the eWOM communities on the consumer product discovery process because many products are only sold online and their consumers are more prone to use online reviews as the primary source for information. Existing literature related to the long tail has shown that eWOM has a positive impact on sales. For example, Brynjolfsson et al. [START_REF] Brynjolfsson | Goodbye pareto principle, hello long tail: The effect of search costs on the concentration of product sales[END_REF] claim that consumers are previously informed about products before buying; thus, niche products are gaining an important share of the overall demand. Likewise, Elberse and OberholzerGee [START_REF] Elberse | Superstars and underdogs: An examination of the long tail phenomenon in video sales[END_REF] show similar results for the comparison of the offline and online sales of DVD and VHS video titles. The authors show that improvements in word of mouth can explain that the increase in the assortment of products offered through online channels shift to a much larger number of niche products. Inversely, Hervas-Draney [START_REF] Hervas-Draney | Word of mouth and taste matching: A theory of the long tail[END_REF] show that word of mouth benefits mostly the winner-take-all or market products and mainstream consumers. Thus, the interaction of users exchanging information about products within eWOM communities creates intricate dynamics in demand. More existing studies of eWOM have found evidence of the superhit effect. For example, Standifird [START_REF] Standifird | Reputation and ecommerce: eBay auction and the asymmetrical impact of positive and negative ratings[END_REF] supports that eWOM promotes the sales of popular products; thus, the head part of the sales distribution becomes thicker. The premise of our study is to clarify these two schools of thought using the distribution of numerous product categories of online reviews of an eWOM community comprising 283,240 subcategories of 68,650 products to identify in which promotes the superhit and which promotes the long tail.

In this regard, our study has found evidence of eWOM as a promoter of both the superhit effect and long tail phenomenon depending on the product categories. However, and following previous studies, the presence of the superhit effect is more extended than the long tail. This result indicates that the long tail phenomenon is closely related to certain categories of products where reviews disseminate new knowledge about items or subcategories unknown for most users. Additionally, we found evidence that the long tail phenomenon is closely related to certain categories of products (e.g., Beauty, Books, Entertainment, Food & Drink, Health, Games, and Music).

The findings are supported by two quantitative methods that mathematically provide evidence about the superhit effect and long tail phenomena. Moreover, our study has important implications for the literature regarding the impact of eWOM on different products.

We demonstrate that the long tail phenomenon can coexist with the super-hit effect depending on the product category. In this regard, research by Lee et al. [START_REF] Lee | The long tail or the short tail: The category-specific impact of eWOM on sales distribution[END_REF] argued that eWOM can change the rule of the long tail theory by differentiating the cases across product types. The authors categorized product types based on the objectivity of product evaluation standards.

Not surprisingly, the Internet is making it easier for consumers to gather information at a low cost and allows them to relay more on the experience of others when they evaluate products.

Again, the increased availability of online reviews about many different products within eWOM communities is the explanatory factor for this phenomenon, given that this online channel allows customers to find more niche products that fit their preferences or to promote a product's popularity. The coexistence of superhit and niche products also means that eWOM has probably expanded an original short tail. Cases such music, entertainment and fashion are examples of product categories where online markets bring the diffusion of new options otherwise unknown by customers. Additionally, online reviews provide not only the description of new options but also the quality of experience. Most reviews focus more on feelings, perceptions and satisfaction than on objective characteristics of products. Therefore, online channels offer more complete information than what can be found in catalogs or advertising.

Managerial implications

In general, the Internet is changing the way consumers behave, and our study contributes to a better understanding of such consumer behavior within online markets. In this regard, our study offers a new perspective on how online information, specifically within an eWOM community, influences the product awareness effect of both superhit and niche products. This disparity leads to a rich-get-richer situation, favoring the products that are already very popular in certain product categories, and leads to a more egalitarian distribution facilitating the formation of the long tail among other product categories. Consequently, as many assortments of products are only sold online and their consumers are more prone to use online reviews as the primary source for information, managers should understand that the underlying economic principles are finding out which products are enclosed in the tail or in the head of the distribution. Additionally, the study provides new insights about potential markets that can be open because of the tail expansion. Companies can shift toward a specialized offer, focusing on products belonging to the tail of the distribution rather than to the head. A prior discovery of those categories exhibiting a long tail can then be used to gain new markets advancing future consumer trends.

Today, any brand or company can, at zero cost, reach many potential consumers via the Internet. This makes it profitable to invest time and effort to create products that might be of interest to even just a tiny segment. Therefore, a strategy of increasing product variety and product information about niche products might permit consumers to discover products that otherwise would be unavailable.

Implications for academics and practitioners

This work has implications for academics and practitioners. From an academic perspective, the study offers the possibility of advancing on the conditions that favor the appearance of the two studied phenomena. Additionally, the distributions of products across categories can change over time, modifying the length of the tail or even the existence of the superhit effect. In general, the Internet is changing the pattern of behavior of consumers, and this study contributes to a better understanding of consumer behavior in online markets.

Due to the current importance of eWOM in businesses and economics, our study has significant implications for multiproduct retailers. A retailer needs to comprehend the impact of eWOM on the distribution of different products to offer the accurate product variety and manage inventory. In this regard, our results show which products of the distribution of product categories are from the long tail or are super hits, allowing specifications of the cases in detail. This implies that practitioners need to be strategic in choosing the product assortment they are offering online. Consequently, online retailers may need to focus more; if their objective is to capture the mass market, they should acquire and manage customers using the superhit or most popular products and focus on marketing those superhit products.

By contrast, if their objective is to use long tail strategies to sell a wider range of goods in smaller quantities, they should focus on broadening their assortment with more niche products.

Likewise, firms can gain leverage of the results to develop better marketing strategies on advertising and promotion of products that consumers are more likely to purchase in the future.

Research limitations

The principal limitation of this paper could be that the methodology has been implemented in only one eWOM community. Nevertheless, it would be possible to extend the two methods (power-law fitting and elbow criterion) to fit the distribution of products in other eWOM communities. Another probable methodological limitation in this study could be the sample of the data set because Ciao UK does not represent the total population but a particular subset of online users. Additionally, users within Ciao might have multiple profiles, or users' profiles might be employed by several people. Although this limitation does not bias the results, they must be understood as applying to a certain set of online users. A further limitation of the study is that a user does not have to provide any purchase proof of the reviewed product to be allowed to write a review. However, writing reviews reports the following benefits to a user: (1) the status benefit that can be achieved from writing reviews, receiving review ratings from other users, rating and commenting on other reviews and referring members to the site and (2) the economic benefit, which, depending on the status a user has within the community and if he/she writes reviews frequently, a certain amount of money is paid by Ciao. Consequently, to obtain such benefits, the users might not be interested in being dishonest. Finally, another limitation of the data is the absence of sales data because this paper draws on online review volume, which is the best available data within an eWOM community. Nevertheless, the context of this study analyzes product diversity of those products that are supposed to be purchased before the user writes any online review.

Future work

Further research can extend these findings by characterizing the niche products across the long tail and superhit products in the head of the distribution. The goal would be to discover some common patterns among niche products through the creation of social network models or association rules and to discover clusters of niche products that can represent a profitable target for retailers. Furthermore, products can be classified as search and experience products. Thus, as future work, we could analyze which type of product is more prone to exhibit the studied behaviors. It would also be interesting to test the validity of the presented models on other eWOM data, where there is available specific information on sales (e.g., Amazon).

(

  DVDs, Education & Careers, Cameras, House & Garden, Office Equipment, Software), 11 with a long tail (Adult Products, Entertainment, Family, Finance, Food & Drink, Games, Health, Household Appliances, Music, Musical Instruments & Equipment, Fashion), and 4 of them with an uncertain long tail (Ciao Café, Shopping, Travel, Electronics)

Figure 1 .Figure 1 .Figure 2 .

 112 Figure1. Example chart representing the power-law distribution of products/events Figure2. Level specification of the main category "Travel" Figure3. Level specification of the main category "Beauty" Figure4. Application of the elbow criterion to the power-law distribution Figure6. Distribution of reviews for some of the main categories in Ciao UK (I) Figure7. Distribution of reviews for some of the main categories in Ciao UK (II) Figure5. Distribution of posted reviews for the 28 main categories

Table 3

 3 Regarding the superhit effect, the p-values from Table1reveal that 7 of the 28 categories among the data sets (Beauty, Books, Cars & Motorcycles, Computers, Internet,

	, 15 of the 28 main categories

Games, Health, Household & Appliances, Music, Musical Instruments, Sports & Outdoors,

Telecommunications) clearly exhibit a long tail behavior as both criteria are accomplished using the two proposed methods.

Table 1 .

 1 Long tail parameters of the 28 main categories of Ciao UK according to the powerlaw method

Table 2 .

 2 Long tail parameters of the 28 main categories of Ciao UK according to the elbow

	method

Table 3 .

 3 Validity of the long tail presence through the consistency of the decision

	rules

long tail short head more generic more specific frequency events

	Music	Yes	Yes	Yes	Yes	True
	Musical Instruments &	Strong	Strong
	Equipment	Yes	Yes

Acknowledgements

This work was supported by Fundación Hergar under the Research Project entitled "Caracterización del fenómeno de la "Cola Larga" en los portales de boca a boca electrónico" with reference AIFH2017/005.

No. of Subcategories Main Categories Figure 1. Distribution of posted reviews for the 28 main categories


Ph.D Roddy Hiram

Ph.D Patrice Naud

Ph.D Feng Xiong

Vincent Doa'a Al-U'datt

Martin G Algalarrondo

Jean-François Sirois

Jean-Claude Tanguay

Stanley Tardif

Nattel

D D S Doa'a Al-U'datt

MD Vincent Algalarrondo

Ph.D Martin G Sirois

MD Jean-François Tanguay

MD Jean-Claude Tardif

MD Stanley Nattel
email: stanley.nattel@icm-mhi.org

Nathalie Mrs

Mrs L'heureux

Mrs Danielle Chantal Saint-Cyr

Gelinas

Right Atrial Mechanisms of Atrial Fibrillation in a Rat Model of Right Heart Disease

Keywords: Arrhythmia, Atrial Fibrillation, Fibrosis, Right Heart Disease, Electrophysiology

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting over 30% of patients diagnosed with heart rhythm dysfunction [START_REF] Saad | Atrial Fibrillation: Current Perspective[END_REF]. Aging, diabetes, obesity, hypertension and a variety of conditions primarily affecting the left ventricle like myocardial infarction, cardiomyopathy and valvular heart disease increase AF-risk [START_REF] Andrade | The clinical profile and pathophysiology of atrial fibrillation: relationships among clinical features, epidemiology, and mechanisms[END_REF]. Extensive work has been performed to study the fundamental basis of the AF-substrate associated with these left-heart conditions [START_REF] Andrade | The clinical profile and pathophysiology of atrial fibrillation: relationships among clinical features, epidemiology, and mechanisms[END_REF][START_REF] Schotten | Pathophysiological mechanisms of atrial fibrillation: a translational appraisal[END_REF][START_REF] Lau | Novel mechanisms in the pathogenesis of atrial fibrillation: practical applications[END_REF]. However, common conditions principally affecting the right heart, including chronic obstructive lung disease [START_REF] Goudis | Chronic obstructive pulmonary disease and atrial fibrillation: An unknown relationship[END_REF], pulmonary hypertension [START_REF] Rajdev | Arrhythmias in pulmonary arterial hypertension[END_REF] and congenital heart disease [START_REF] Drakopoulou | Arrhythmias in adult patients with congenital heart disease and pulmonary arterial hypertension[END_REF], also increase AF-risk, but the underlying mechanisms are much less well-understood. The objectives of this study were: i.) to evaluate the effect of right heart disease (RHD) on atrial arrhythmia susceptibility in a rat model; ii.) to determine the mechanisms underlying arrhythmogenesis with the use of optical mapping; and iii.) to assess the potential biochemical basis with the use of transcriptomic analyses. For some studies, we compared right (RA) and left (LA) atrial gene-expression changes associated with RHD to those resulting from AF-promoting left heart disease (LHD) caused by myocardial infarction (MI).

Methods

Detailed Methods are provided in the Online Supplement.

Model of RHD

Male Wistar rats weighing 200-275 g were obtained from Charles River Laboratories (Montreal, Quebec). Rats were randomly assigned to control (vehicle-treated) or monocrotaline (MCT) groups (n=32/group). MCT-animals received a single i.p. dose (60 mg/kg) of MCT. On day 21 post-MCT, a transesophageal electrophysiological study (EPS) was performed under 2%isoflurane anaesthesia, to determine AF vulnerability and duration. The heart was then excised and Langendorff-perfused for optical mapping (n=12) or dissected for histological/biochemical studies. RV hypertrophy was assessed based on Fulton's Index (RV mass/[LV+septal mass]).

Atrial Remodeling Due to Acute MI

Male Wistar rats (200-275 g) were injected subcutaneously (SC) with buprenorphine (0.03 mg/kg) and anaesthetized with 2%-isoflurane. The left anterior descending coronary artery was ligated via left thoracotomy. Buprenorphine (0.03 mg/kg) was injected SC 6 and 12 hours postoperatively.

Echocardiography

Echocardiograms were obtained under 2%-isoflurane anaesthesia at baseline, day-14 and day-21 using a phased-array 10S probe (4.5 to 11.5 MHz) in a Vivid 7 Dimension system (GE Healthcare Ultrasound, Horten, Norway).

Transesophageal Stimulation

EPS was performed in vivo via transesophageal stimulation with a 4F quadripolar catheter (2-mm interpolar distances; St. Jude Medical #401993). To assess atrial arrhythmia inducibility, 50-Hz burst pacing was applied for 3 s, with twelve bursts separated by 2-s intervals [START_REF] Reil | Aldosterone promotes atrial fibrillation[END_REF]. AF was defined as a rapid (>800 beats/min) irregular atrial rhythm lasting ≥1 s. Atrial flutter (AFl) was defined as a regular atrial tachyarrhythmia between 600 and 800 bpm. AFduration was the mean duration of all induced AF-episodes.

Hemodynamic Measurements

A 2-F pressure-transducer catheter (Science P catheter-RAT) was used to measure aortic blood pressure (BP) and LV systolic pressure (LVSP). RV systolic pressure (RVSP) was measured with a catheter introduced via the right jugular vein.

Optical Mapping

The heart was excised and perfused via the aorta with Krebs solution at 10 ml/min and 37°C. After 20 minutes for stabilization, a recirculating solution containing 15-µM blebbistatin was used to suppress mechanical contraction. Di-4-ANEPPS (10-µM, 0.1 ml) was injected.

Fluorescence signals were recorded at 2 kHz with a charge-coupled device focused on a region up to 8×8 mm in the RA or LA free-wall. Effective refractory period (ERP) was measured with programmed stimulation at a basic cycle length (BCL) of 150 ms. AF-inductions were performed at BCLs 300, 250, 150, 100, 80 and 60 ms (3 s each) and with 25-Hz burst-pacing.

Conduction velocity (CV) and action potential duration to 80% repolarization (APD80; average for all pixels) were determined as previously described [START_REF] Xiong | Wavelet analysis of cardiac optical mapping data[END_REF].

Histology

Formalin-fixed samples were stained with Masson's Trichrome. Images were analyzed (blinded to rat-group) to quantify fibrous-tissue content. Lung-samples were fixed in 10%formalin to evaluate pulmonary-artery medial wall-thickness.

PCR and Gene Microarray Analysis

Quality-control and differentially-expressed genes were assessed with Transcriptome Analysis Console (TAC) 4.0. The significance filter was set at P<0.05 with a fold-change >2 needed for further analysis. Signalling pathways were obtained with KOBAS 3.0 web-server for enrichment analysis [START_REF] Xie | KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases[END_REF][START_REF] Wu | KOBAS server: a web-based platform for automated annotation and pathway identification[END_REF]. Biological process, cellular component, and molecular function were analyzed with DAVID database [START_REF] Huang | Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists[END_REF][START_REF] Huang | Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources[END_REF]. Hierarchical clustering was performed with Cluster 3.0 [START_REF] De Hoon | Open source clustering software[END_REF] and Treeview (15) software.

Drugs and Reagents

Monocrotaline was obtained from Sigma-Aldrich (St. Louis, MO). Blebbistatin and di-4-ANEPPS were obtained from Cedarlane (Burlington, Ontario). Collagen1α1, collagen3α1, Cx40, Cx43, FN1, αSMA, PDGFRα, PDGFRβ, TGFβ1, MMP2, MMP9, KCNA5, KCNJ2, KCNQ1, CACNA1C and GAPDH probes were obtained from ThermoFisher Scientific (Waltham, Massachusetts).

Statistical Analysis

Statistical analysis was performed with Student's t-test (for 2-sample analyses only) or one-way or two-way ANOVA. Post-hoc Tukey or Bonferroni-corrected Student t-tests were applied when analyses of variance revealed significant group effects. Categorical variables like AF-inducibility were analyzed with the Fisher exact test. Results are expressed as mean±S.E.M. Differences were considered statistically significant for two-tailed P-values< 0.05.

Results

Cardiac Structural and Hemodynamic Remodeling

Figure 1A shows pressure recordings from the left ventricle (LV) and aorta in control and MCT-rats 21 days after injection. MCT-rats had reduced LV and arterial BP. Figure 1B shows RV-recordings in the same rats, indicating substantially increased RVSP with MCT. Mean data in Figure 1C show a statistically significant, ~30% decrease in BP and LVSP and a >2-fold increase in RVSP.

PA wall-thickness was analyzed histopathologically (Online Figure 1A), showing significant increases in MCT-treated rats (44.1±0.7 μm) versus controls (11.8±0.8 μm; Figure 1D). The RV was hypertrophied in MCT-rats (Online Figure 1B). Fulton's Index was significantly increased from 0.19±0.04 (control) to 0.41±0.03 in MCT-rats (Figure 1E). 3C). These included significant decreases in TAPSE, tricuspid annulus motion velocity and AT/RVET-ratio, along with important tricuspid regurgitation in all MCT-rats. LV function indices showed slight but significant reductions in LV-dimensions and increased LV ejection-fraction in MCT-rats (Online Table 1).

AF-Vulnerability and ECG Parameters

Transesophageal stimulation (Online Figure 4) induced AF/AFl in all MCT-rats but rarely in controls (Figure 2A). Mean AF-duration increased from 2.2±0.3 s in control to 11.2±3.2 s (P<0.05) in MCT-rats. AFl was induced only in MCT-rats (2 with only AFl, 3 with episodes of both AFl and AF), with a mean duration of 135±77 s. ECG-analysis revealed significant increases in P-wave duration (Figure 2B), P-P (Figure 2C) and QT intervals (Figure 2F), with unchanged PR-interval and QRS-duration (Figure 2D, Figure 2E), in MCT-rats.

In Situ EPS and Optical Mapping

Langendorff-perfused hearts were subjected to in situ EPS and optical mapping. AF was readily induced in MCT-rats (Figure 3A). AF-inducibility was substantially greater in MCT-rats (11/12 showing induced AF; 92%) than controls (2/12, 17%, P<0.001; Figure 3B), as was AFduration (Figure 3C): 8.0±1.0 s (control) versus 51.4±19.2 s (MCT). RA conduction velocity was slowed in MCT-treated rats, with slowing increasing at shorter BCLs closer to those of AF (Figure 4A). RA APD showed statistically significant increases in MCT-treated rats (Figure 4B), with changes corresponding to significant increases in ERP (Figure 4C). RA optical mapping revealed evidence of rotor activity maintaining AF. Stable rotors were observed during AF in 3 MCT-rats; in addition, one rat with AFl but no AF showed macroreentry with a single stable rotor. An example of rotor activity during AF is illustrated in Figure 5A, based on transmembrane-potential fluorescence over 1 cycle (Figure 5B) and phase maps covering 2 cycles (Figure 5C).

Atrial Structural Remodeling

Atrial structural remodeling, particularly fibrosis, is a common finding in many forms of AF [START_REF] Andrade | The clinical profile and pathophysiology of atrial fibrillation: relationships among clinical features, epidemiology, and mechanisms[END_REF]. Figure 6 shows an analysis of atrial structure in control and MCT rat RA (top) and LA (bottom). MCT increased both RA fibrous-tissue content (over 5-fold, P<0.001; Figure 6A) and dimension (Figure 6B). In the LA, MCT also increased fibrous-tissue content (about 2-fold, P<0.001; Figure 6C) but did not cause dilation (Figure 6D).

Comparison with AF in LHD

In order to obtain additional insights into the pathophysiology of AF associated with RHD, we repeated selected observations in rats with LHD associated with acute MI. Significant structural remodeling was noted in MI-rats, with fibrous-tissue content of 14.6±1.8% and 10.8±2.2% in LA and RA respectively. Figure 7A illustrates LA conduction-changes in MCT and MI rats. MI-rats showed major slowing in LA conduction, whereas modest, non-significant conduction velocity decreases were noted in MCT-rats. LA ERP was significantly increased in MCT but reduced in MI (Figure 7B), with qualitatively similar changes in APD (Figure 7C).

EPS with LA burst-pacing induced AF (Online Figure 5) in 5/6 MCT-rats and 6/6 MI-rats, with mean AF-duration of about 5 s and 20 s in MCT and MI rats respectively (Figure 7D and Figure 7E).

Expression of Specific Genes Related to Electrophysiological Changes

The expression of selected genes encoding a range of proteins that govern cardiac electrophysiology were examined by qPCR; others were available from the gene microarray analysis. Atrial fibrosis is a prominent cause of conduction-changes underlying AF [START_REF] Li | Promotion of atrial fibrillation by heart failure in dogs: atrial remodeling of a different sort[END_REF]. The RA messenger-RNA expression of fibrosis-related genes Col1α1, Col3α1, Fn1, Acta1 (α-SMA), Mmp2, and Mmp9 (Figure 8) was upregulated in MCT-rats, with Col1α1 and Mmp2 also significantly increased in MI-rat LA. No significant increases were observed in LA of MCT-rats or RA of MI-rats. The profibrotic signaling-molecule genes Pdgfra, Pdgfrb, and Tgfβ1 were upregulated in RA of MCT-rats; of these, the only upregulated signaling gene in MI-rats was Tgfβ1 in LA and RA (Online Figure 6).

Connexin-proteins form the hemichannels responsible for cell-to-cell coupling and can be dysregulated in AF [START_REF] Andrade | The clinical profile and pathophysiology of atrial fibrillation: relationships among clinical features, epidemiology, and mechanisms[END_REF][START_REF] Schotten | Pathophysiological mechanisms of atrial fibrillation: a translational appraisal[END_REF][START_REF] Lau | Novel mechanisms in the pathogenesis of atrial fibrillation: practical applications[END_REF]. Connexin40 and 43 are the 2 principal connexins in atrial tissue. Both qPCR and gene microarray data were available: connexin43 was downregulated on both in MCT RA (Online Figure 7). Significant connexin43-downregulation was seen with qPCR in both RA and LA for both MCT and MI rats. For connexin40, the only consistent change was upregulation in MCT-RA, which was statistically significant only on qPCR.

We also examined changes in mRNA-expression with qPCR for a variety of ion-channel genes reported to be dysregulated in AF [START_REF] De Hoon | Open source clustering software[END_REF]: Cav1.2 (Cacna1c), Kir2.1 (Kcnj2), Kv1. 5 (Kcna5) and Kcnq1. All were downregulated in LA and RA of MI-rats (Online Figure 8); only Kcnq1 was significantly reduced in MCT-rats. The expression of a variety of additional Ca 2+ -handling genes was assessed from gene microarray data (Online Figure 9). The most consistent changes were seen in the ryanodine-receptor (Ryr2), which was significantly downregulated in both RA and LA of MCT and MI rats. MCT RA showed the largest number of dysregulated genes, with Ryr2, sarcolipin (Sln, an atrial-specific Ca 2+ -binding protein) and the sodium-calcium exchanger Ncx1 all significantly downregulated in MCT-rat RA. Sln was also reduced in MI-rat LA, albeit to a lesser extent than in MCT RA. Finally, the sodium-channel α-subunit gene Scn5a was also downregulated in MCT-RA and MI-LA, potentially contributing to conduction-slowing in these regions.

Transcriptomic Analysis

In order to gain insight into the gene programs activated in the atria of MCT and MI rats, we performed pangenomic transcriptome analysis based on the microarray data. In MCT-rats, 917 genes were significantly dysregulated (444 down; 473 up) in the LA versus 2690 genes (1419 down; 1271 up) in the RA. In MI-rats, 2371 genes were dysregulated (1075 down; 1296 up) in the LA, versus 2000 genes (817 down and 1183 up) in the RA. Consistent with the underlying pathophysiology, the most strongly dysregulated transcriptome patterns were noted in RA from MCT-rats and LA from MI-rats (Figure 9). Gene-categories classified as biological process, cellular component and molecular function were identified, and revealed that RA from right-heart diseased rats (MCT) and LA from left-heart diseased rats (MI) shared a high level of differentially expressed gene-groups such as those involved in extracellular matrix, focal adhesion, membrane, proteinaceous extracellular matrix, extracellular exosome and/or cell adhesion that are directly related to fibrogenesis.

RA and LA samples were further analyzed to identify the most statistically significant differentially-expressed genes in rats with RHD (MCT) and LHD (MI) compared to control (Online Figure 10). The left side of the figure shows expression heat-maps in all RA-(top) and LA-(bottom) samples for the genes that were most dysregulated in MCT-rat RA. Cluster (a) genes in panel A were downregulated in MCT RA and cluster (b) genes upregulated. Many of the strongly dysregulated genes in RA of MCT-rats shown in A were similarly dysregulated in LA of MI-rats shown in B; the same genes showed less dysregulation in MI-RA and MCT-LA.

The right panel shows a similar analysis for the most significant differentially expressed genes in MI-rat LA. Once again, the RA of MCT-rats showed a similar dysregulation pattern (panel C) to that of LA in MI-rats (D). Online Figure 11 shows a Venn diagram for the most dysregulated genes in MCT-rat RA and MI-rat LA. Seven common genes (Acta1, Col8a1, Myl3, Myh7, Postn and Thbs1), known to be involved in cardiac hypertrophy, fibrosis and thrombogenesis, were upregulated in LA from MI and RA from MCT; Art1, involved in apoptosis and immunoprotection, was downregulated in MI LA and MCT RA.

Discussion

The present study addresses the AF-susceptibility changes and underlying mechanisms occurring in a well-established rat model of RHD (Central Illustration). Central elements included RA, and to a lesser extent LA, fibrosis and conduction abnormalities that stabilized reentry. Transcriptomic analysis indicated activation of hypertrophic, proinflammatory and profibrotic pathways that shared many motifs with profibrillatory LA remodeling caused by LVdysfunction due to acute MI.

RHD and AF

It is widely believed that the LA plays a predominant role in AF, and there is extensive supportive clinical and experimental evidence, particularly in studies of LHD-models (2). However, AF can also be quite prominent in RHD. Chronic obstructive pulmonary disease is an important risk factor for AF (5, 7), with the one-second forced expiratory volume (FEV1) being an independent predictor of new-onset AF and AF hospitalization [START_REF] Buch | Reduced lung function and risk of atrial fibrillation in the Copenhagen City Heart Study[END_REF]. Supraventricular arrhythmias are a common complication in adults with congenital heart disease and pulmonary hypertension (PH), with AF constituting a substantial proportion and being a strong independent mortality risk factor [START_REF] Drakopoulou | Arrhythmias in adult patients with congenital heart disease and pulmonary arterial hypertension[END_REF]. New-onset AF/atrial flutter has a five-year incidence of about 25% in patients with primary or chronic thromboembolic PH [START_REF] Olsson | Atrial flutter and fibrillation in patients with pulmonary hypertension[END_REF], heralding increased death rates [START_REF] Olsson | Atrial flutter and fibrillation in patients with pulmonary hypertension[END_REF][START_REF] Wen | Frequency of supraventricular arrhythmias in patients with idiopathic pulmonary arterial hypertension[END_REF][START_REF] Bandorski | Evaluation of the prognostic value of electrocardiography parameters and heart rhythm in patients with pulmonary hypertension[END_REF][START_REF] Wanamaker | Atrial Arrhythmias in Pulmonary Hypertension: Pathogenesis, Prognosis and Management[END_REF]. Finally, RV dysfunction is one of the strongest predictors of AF-occurrence in patients with acute decompensated heart failure [START_REF] Aziz | Right ventricular dysfunction is a strong predictor of developing atrial fibrillation in acutely decompensated heart failure patients, ACAP-HF data analysis[END_REF]. Thus, there are extensive data pointing to the potential importance of RHD as a factor leading to AF.

Mechanisms by which RHD Leads to AF

Despite the clinical evidence noted above, relatively little is known about how RHD causes AF. Here, we show that in a rat MCT-induced PH model: 1.) AF inducibility and sustainability are greatly enhanced; 2.) RA conduction slowing that stabilizes re-entrant activity is a prominent mechanism; 3.) Tissue fibrosis is substantially enhanced, particularly in the RA, and likely underlies the conduction changes; 4.) Tissue remodeling is associated with prominent transcriptomal reprogramming. The transcriptomal remodeling associated with RHD involves a large number of systems associated with hypertrophic, proinflammatory and profibrotic responses.

Relatively little prior work has been performed to study the potential mechanisms linking RHD to AF. We were able to identify one study that examined MCT-induced PH in a beagle dog model [START_REF] Zhao | Effects of Intrinsic and Extrinsic Cardiac Nerves on Atrial Arrhythmia in Experimental Pulmonary Artery Hypertension[END_REF]. The authors noted an increased window of vulnerability for AF-induction associated with increased sympathetic nerve and beta-adrenoceptor density. Koyama The present study is the first transcriptomic analysis of RA/LA changes in a RHD model.

The results show much more substantial changes in the RA versus LA of MCT-rats (Figure 9).

The extent of gene-expression dysregulation in MCT RA and MI LA was similar, compatible with their roles as primary AF-drivers respectively. Deshmukh et al previously analyzed transcriptional changes in LA-appendage surgical samples from patients with no AF-history, with a history of AF but in sinus rhythm at the time of surgery, and with a longstanding and persistent history of AF [START_REF] Deshmukh | Left atrial transcriptional changes associated with atrial fibrillation susceptibility and persistence[END_REF]. They noted that AF-susceptibility was characterized by dysregulation of targets related to inflammation, oxidation and cellular stress responses. They analyzed transcription factor targets and noted specific patterns of dysregulation, which might be interesting to pursue in subsequent phases of this work. There is evidence that inflammation may be a central but poorly understand contributor to AF-pathophysiology [START_REF] Hu | Inflammation and the pathogenesis of atrial fibrillation[END_REF][START_REF] Yao | Enhanced Cardiomyocyte NLRP3 Inflammasome Signaling Promotes Atrial Fibrillation[END_REF]. In the present study, Reg3b was the most up-regulated gene in MCT-rat RA versus control. Reg3b is involved in inflammatory responses, regulating macrophage accumulation in response to myocardial ischemia [START_REF] Lörchner | Myocardial healing requires Reg3β-dependent accumulation of macrophages in the ischemic heart[END_REF]. Our gene microarray assay data also showed that Cxcl1 and Cxcl2, two proinflammatory chemokines expressed by macrophages, were up-regulated in the RA and LA of MCT-rats (Online Figure 10). A recent study reported that the CXCL1-CXCR2 axis regulates monocyte infiltration and angiotensin II-induced cardiac hypertrophy and remodelling [START_REF] Wang | CXCL1-CXCR2 axis mediates angiotensin II-induced cardiac hypertrophy and remodelling through regulation of monocyte infiltration[END_REF]. Finally, recent work has implicated cardiomyocyte NLRP3-inflammasome signaling in the AF-substrate, leading to tissue fibrosis, aberrant Ca 2+ -release promoting ectopic activity and upregulation of K + -channels causing APD-abbreviation [START_REF] Yao | Enhanced Cardiomyocyte NLRP3 Inflammasome Signaling Promotes Atrial Fibrillation[END_REF]. We therefore examined the expression-changes corresponding to key NLRP3-related genes based on our microarray data.

The results, shown in Online Figure 12, indicate upregulation of Casp1 and Casp8 in MCT-rat RA, Casp1 in MCT-rat LA, Casp1 and IL-1b in MI-rat LA. In addition, Nlrp3 and IL-1b mean mRNA expression-values were higher in MCT-RA than control, but there was considerable variability in the results and no statistically significant difference.

MCT-rats had increased inducibility and duration of AF despite increased RA APD and RA and LA ERP, likely because of fibrosis-associated conduction abnormalities. In contrast to MCT-rats, MI-rats had reduced LA ERP and APD, consistent with significant decreases in Ltype Ca 2+ -channel (Cacna1c) mRNA expression in MI-rats (Online Figure 8).

Potential Limitations

The MCT model has been used to study PH for over 50 years [START_REF] Wang | CXCL1-CXCR2 axis mediates angiotensin II-induced cardiac hypertrophy and remodelling through regulation of monocyte infiltration[END_REF] and is the most widely used method for this purpose. While MCT produces PH in a predictable way, it has limitations in reproducing the specific pathophysiology of idiopathic PH [START_REF] Lalich | Pulmonary arteritis produced in rat by feeding Crotalaria spectabilis[END_REF]. For the present study, we wanted an animal model that could reliably and reproducibly induce RHD [START_REF] Nogueira-Ferreira | Exploring the monocrotaline animal model for the study of pulmonary arterial hypertension: A network approach[END_REF], to define the consequences for AF-susceptibility and the underlying pathophysiology, and were not aiming to study the particularities of vascular pathology in PH. The hemodynamic, tissue remodeling and echocardiographic consequences are likely related to those that would be seen with any form of RHD, whether due to congenital heart disease, primary diseases of the pulmonary vasculature or parenchymal lung disease. Nevertheless, the specific clinical manifestations would be expected to vary with the precise pathology, the rate of its development, and the presence of concomitant conditions, so our rat model does not precisely mimic clinical forms of RHD.

The principal AF-promoting feature appeared to be RA conduction abnormalities associated with prominent fibrosis, along with RA dilation. Fibrous-tissue content increased dramatically in the RA and was accompanied by quite striking conduction abnormalities, especially at rapid rates close to those of AF (Figure 3A). LA changes were less striking, with lesser fibrosis and much more limited conduction changes (Figure 7A) than in the RA.

However, there was a significant increase in LA fibrous-tissue content in MCT-rats, suggesting that fibrosis was due not only to local abnormalities in atria directly exposed to hemodynamic stress, but that some other form of more remote signaling (such as that due to neurohumoral changes) might be at play. The RA action-potential changes we noted in MCT-rats consisted principally of modest APD-prolongation, which was accompanied by parallel changes in ERP.

These would be expected to make reentry/rotor-formation less likely [START_REF] Nattel | Demystifying rotors and their place in clinical translation of atrial fibrillation mechanisms[END_REF] and thus not to promote AF, contrasting with the LA APD-abbreviation occurring in MI-rats, which might have contributed to their longer AF-durations (Figure 7E).

Conclusions

We have assessed the atrial remodeling in a rat model of RHD, identifying strong increases in AF-susceptibility associated with prominent RA remodeling. There are common motifs and some interesting differences compared to the AF-substrate in rats with LVD post-MI.

These findings emphasize the importance of RHD as a predisposing condition for AF, provide new mechanistic insights and point to new approaches and tools for therapeutic innovation.

CLINICAL PERSPECTIVES

Competency in Medical

Functional

  consequences of right-heart remodelling accompanying PH were confirmed with echocardiographic analyses of tricuspid valve movement and function (Online Figure 2), pulmonary artery flow pattern (Online Figure 3A) and flow index (Online Figure 3B), right-ventricular wall thickness and right-ventricular systolic function (Online Figure

  et al observed RA hypertrophy and a slight decrease in CACNA1 mRNA in rats with MCT-induced PH (24). Medi et al studied electroanatomical remodeling in PH patients, observing phenomena very similar to what we noted in our experimental studies: PH patients exhibited slower RA conduction, reduced electrogram voltage and electrically silent areas suggesting fibrotic scar, and increased AF-inducibility (25). John et al. studied mitral stenosis patients and noted extensive changes compatible with slow conduction and tissue fibrosis in both the LA and RA (26). While AF is generally attributed to the LA in mitral stenosis, the RA could conceivably be an important contributor in patients with severe secondary RHD, particularly in longstanding cases with marked PH.

  Knowledge: The right atrium plays a central role in sustaining atrial fibrillation in an animal model of right heart disease through mechanisms that involve atrial conduction abnormalities caused by atrial fibrosis. Translational Outlook: The next steps in clinical translation are to identify key signaling mechanisms leading to right atrial remodeling that might lead to development of novel approaches to preventing AF associated with right heart disease.

Figure 1 .

 1 Figure 1. Hemodynamic Measurements. Representative recordings of (A) Left ventricular

Figure 2 .

 2 Figure 2. Atrial Arrhythmia Inducibility and Electrocardiogram Analyses. (A) Percentage

Figure 3 .

 3 Figure 3. In situ AF-induction. (A) Atrial electrogram recordings in response to burst-pacing in

Figure 4 .

 4 Figure 4. Optical Mapping Data. (A) Left: Right atrial (RA) activation maps at basic cycle

Figure 5 .

 5 Figure 5. Rotor Activity. (A) Upper panel shows a picture of the RA area delimited by a yellow

Figure 6 .

 6 Figure 6. Fibrosis Quantification. Histological analysis of right ((RA) upper panels) and left

Figure 7 .

 7 Figure 7. LA Electrophysiological Remodeling. (A) Left: left atrial (LA) activation maps at

Figure 8 .

 8 Figure 8. Fibrosis Marker Expression. essenger RNA expression, as measured by qPCR,

Canadian Institutes of Health Research and Heart and Stroke Foundation of Canada.

Central Illustration. Dysfunction Induced by Right Heart Disease (RHD) Leading to Atrial

Fibrillation. MCT-induced pulmonary hypertension promotes severe right-ventricular hypertrophy due to pressure overload, along with tricuspid regurgitation, which cause right atrial (RA) pressure/volume loading, hypertrophy and dilation. In response to chronic RA mechanical loading, tissue fibrosis and electrical abnormalities, including altered conduction and repolarization properties, are observed. RA stress is also associated with increased expression of genes involved in hypertrophy, inflammation, apoptosis, and fibrosis. Together, these abnormalities constitute a proarrhythmic substrate that increases AF-vulnerability.