The pragmatic differences between grammatical and lexical evidentiality: A corpus-based study of Tibetan and English

Keywords: Evidentiality Tibetan English Grammaticalization Frequency Optionality ADJ, adjective, ADV, adverb, AUX, auxiliary, C, complementizer, CIS, cislocative, COMP, comparative, CON, conjunction, COP, copula, CPL, completive, DAT, dative, DEM, demonstrative, DIR, direct perception, DUR, durative, EGO, egophoric, EPI, epistemic, ERG, ergative, FACT, factual, GEN, genitive, H, honorific, HAB, habitual, HSAY, hearsay, INCPL, incompletive, INDF, indefinite, INF, inferential, INT, interrogative, LOC, locative, LV, light verb, NEG, negative, NMLZ, nominalizer, NP, noun phrase, PF, perfective, PHA, phatic, p.p., past participle, PRO, pronoun, S, sentence, V, verb

The paper examines to what extent expressing information sources with a fully grammaticalized evidential system or with lexical means may have a different pragmatic impact in conversation. A contrastive corpus of Tibetan (TSC) and English (CSC/LAC) allows me to investigate several dimensions: frequency, semantic schematicity, optionality, economy, and information hierarchy. The data from the contrastive corpus indicate that Tibetan evidentials are on average 6.7 times more frequent than English evidentials. Tibetan evidentials are also functionally more schematic, since English evidentials usually contain more semantic features. This compels English speakers to be more specific when referring to their information sources. Grammatical evidential systems may be less optional than lexical systems, but the degree of optionality differs depending on the linguistic level. The morpho-syntactic obligatoriness of many Tibetan evidentials may indeed be compensated by the availability of evidentially neutral forms in the same paradigm. However, evidentiality seems to be pragmatically less optional in Tibetan than in English. Tibetan evidentials are also more economical on a morphophonetic, syntactic, and cognitive level. Finally, all these parameters influence the informational status of evidentials. Because they are more frequent, schematic, obligatory, and economical, Tibetan evidentials appear more backgrounded.

Introduction 1

Research on evidentiality is rapidly expanding in two main directions. One line of study traditionally focuses on languages with highly grammaticalized evidential paradigms, while the other examines languages which mainly express information sources lexically. These two perspectives have been prolific in the past two decades. Numerous monographs and edited volumes have given us a detailed cross-linguistic documentation of languages with complex grammatical systems encoding evidentiality (Aikhenvald & Dixon, 2003;[START_REF] Aikhenvald | Evidentiality[END_REF]ed., 2018;[START_REF] Aikhenvald | The web of knowledge: Evidentiality at the cross-roads[END_REF]Gawne & Hill, eds., 2017). A comparable amount of work has been published on the (semi-)lexical expression of information sources in various language families, notably Romance, Germanic, and Slavic languages (Diewald & Smirnova, eds., 2010;Marín-Arrese et al., eds., 2017;Foolen et al., eds., 2018;Wiemer & Marin-Arrese, eds., 2022). However, these two branches of study rarely meet, and this paper aims to connect work in classical typology and more pragmatic approaches based on highly investigated languages. This study will be based on a contrastive corpus of two languages with radically different evidential systems, namely Tibetan and English, in their standard, contemporary forms.

Although all Tibetic languages present grammaticalized evidentials, my analysis will focus on standard spoken Tibetan, which is particularly relevant when working on evidentiality for several reasons. It is a 'complex evidential language' [START_REF] Tournadre | Towards a new approach to evidentiality: Issues and directions for research[END_REF], as it possesses numerous fully grammaticalized forms encoding information sources, such as the inflected copulas yod, 'dug, the verbal suffixes -song, -bzhag, or the enclitics -za, -ze, etc. [START_REF] Delancey | Lhasa Tibetan evidentials and the semantics of causation[END_REF]Tournadre, 1996: 220-238;[START_REF] Tournadre | Arguments against the concept of 'conjunct'/'disjunct' in Tibetan[END_REF]2017;[START_REF] Garrett | Evidentiality and assertion in Tibetan[END_REF]: 22-207. Author, 2014: 112-144). Moreover, Tibetan grammar includes evidential forms that encode the three main evidential categories: direct perception, inference, and hearsay. Finally, among the complex evidential languages, Tibetan probably has the greatest amount of synchronic and diachronic data available. Several scholars have offered in-depth linguistic descriptions of the language, a variety of corpora have been collected, and written Tibetan extends from the 8 th to the 21 st century, offering a unique opportunity to investigate the grammaticalization of evidentiality in detail [START_REF] Saxena | Aspect and evidential morphology in Standard Lhasa Tibetan: A diachronic study[END_REF][START_REF] Hill | ḥdug as a testimonial marker in Classical and Old Tibetan[END_REF][START_REF] Gawne | Egophoric evidentiality in Bodish languages[END_REF][START_REF] Oisel | On the origin of the Lhasa Tibetan evidentials song and byung[END_REF][START_REF] Zeisler | Evidence for the development of 'evidentiality' as a grammatical category in the Tibetic languages[END_REF].

Conversely, English is often presented as a textbook example of languages lacking grammatical evidentiality (Aikhenvald, 2004: 10;[START_REF] Whitt | Inter)Subjectivity and evidential perception verbs in English and German[END_REF]. Although this claim must be qualified (Author, 2022), the English evidential system is indeed overwhelmingly more lexical than grammatical. English is an ideal candidate for a contrastive analysis, since probably no language has been described with as much depth and detail in synchrony and diachrony.

Moreover, the mass of new data that has been accumulating in the past decades makes the analysis of subtle pragmatic phenomena more evidence-based.

The research on grammatical and lexical evidentiality has recently seen an unprecedented development leading to a better cross-linguistic understanding of the notion on several linguistic levels. However, the pragmatic differences between expressing evidentiality in a language which possesses a grammatical paradigm for it and a language with very limited grammatical evidentiality deserve more attention. With detailed corpus data, this article contributes to filling this gap by investigating the implications of radically different evidential systems for a speaker's discursive choices. The paper is organized as follows. Section 2 offers a definition of evidentiality, and presents some of the current debates on its morpho-syntax and semantics.

Section 3 introduces the corpora that were collected specifically to contrast Tibetan and English evidential systems. Section 4 presents how evidentiality manifests itself in the two languages.

It illustrates the criteria that linguistic forms have to meet to be considered evidentials. Section 5 discusses the main findings, and examines how Tibetan and English evidentiality are pragmatically different. In section 6, I will formulate my conclusion.

A definition of evidentiality

The dominant definition of evidentiality is probably the one adopted in [START_REF] Aikhenvald | Evidentiality[END_REF]ed., 2018), i.e. 'the grammatical marking of information sources'. However, alternative definitions have been proposed by several linguists [START_REF] Squartini | The internal structure of evidentiality in Romance[END_REF][START_REF] Tournadre | Towards a new approach to evidentiality: Issues and directions for research[END_REF]Author, 2014: 31-34;[START_REF] Boye | Evidentiality: The Notion and the Term[END_REF], and many points are still debated.

First, 'information source' may not be the best term to describe what evidentials encode.

'Source' usually refers to the specific work or person that supplies information (e.g., definition in the OED), while evidentials possess a more abstract meaning. They refer rather to the speakers' types of access to the information they are sharing, by specifying if a statement relies on direct perception, inference, or hearsay.2 Although I do not see 'information sources' as the most appropriate label, I will still use this term, because it is relatively concise and largely dominant in the literature. It should be taken as technical terminology referring to the type of channel through which the information was accessed by a speaker.

Secondly, several scholars argue that evidentiality should not be limited to grammatical morphemes but should be seen as a semantic domain encoded by various forms that may be located at any point along the lexicon-grammar continuum [START_REF] Squartini | Investigating a grammatical category and its lexical correlates[END_REF][START_REF] Cornillie | The continuum between lexical and grammatical evidentiality: A functional analysis of Spanish parecer[END_REF]Author, 2014: 33;[START_REF] Wiemer | Introduction[END_REF]. I would argue that it is indeed heuristically more relevant to adopt the latter definition. Firstly, although Aikhenvald rightfully points out the striking differences between languages with complex evidential paradigms and those which mainly refer to information sources through their lexicons, drawing a firm line between what is lexical and what is grammatical is problematic. The literature on grammaticalization has discussed many competing criteria, and has shown how grammatical forms emerge from the lexicon in a step-by-step fashion [START_REF] Lehmann | Revision of Thoughts on grammaticalization: A programmatic sketch, 1[END_REF][START_REF] Lehmann | Revision of Thoughts on grammaticalization: A programmatic sketch, 1[END_REF]; Traugott & Trousdale, eds., 2010;Narrog & Heine, eds., 2011). Secondly, if one can talk about the lexical expression of time or modality, I do not see why one should not refer to the lexical expression of evidentiality. In order to investigate how evidentiality may differ when it is mainly rendered by grammatical or lexical forms, I need to define it as a semantic notion. My definition of evidentiality is thus morphologically open, but semantically strict: the expression of the mode of access to the main information stated in a proposition.

Several scholars have used the notion of evidentiality to cover a wide range of phenomena, such as epistemic modality (i.e., the probabilistic evaluation of the information), subjectivity (i.e., the presentation of the information as the speaker's sole responsibility), or (ad)mirativity (i.e., the unexpectedness of the information) [START_REF] Chafe | Evidentiality in English conversation and academic writing[END_REF][START_REF] Friedman | Evidentiality in the Balkans: Bulgarian, Macedonian, and Albanian[END_REF][START_REF] Palmer | Mood and modality[END_REF]Infantidou, 2001;[START_REF] Nuyts | Subjectivity as an evidential dimension in epistemic modal expressions[END_REF][START_REF] Whitt | Inter)Subjectivity and evidential perception verbs in English and German[END_REF]. In line with my narrow definition, however, I only count as an evidential a form that encodes a type of information source explicitly. This semantic feature must be inherent (i.e., not due to a mere implicature), and must have scope over the main predication, which excludes statements that may seem evidential but do not have a propositional scope, such as 'I saw it' (see the criteria presented in [START_REF] Anderson | Evidentials, Paths of Change, and Mental Maps: Typologically Regular Asymmetries[END_REF]).

I will now present how I collected a corpus for Tibetan and English before illustrating these definitional criteria in the two languages under study (4.1 and 4.2).

Corpus collection and methodology

In order to conduct an in-depth contrastive study, the first indispensable step for me was to collect a corpus of comparable data that is adapted to my research objectives. I used the exact same methodology with the aim of eliciting as many varied evidentials as possible in semi-guided conversations. I asked pairs of L1 speakers to ask each other questions related to various types of information sources. The questions dealt with the news, dreams, recent and distant memories, events that happened when the participants were infants or before they were born, etc. I also resorted to three behavioural tasks that proved useful to elicit markers of direct perception, inference, and hearsay: identifying the subject of mysterious pictures, recognizing indistinct sounds, and reporting the content of a comic strip (for further information, see Author 2014: 76-83). The Tibetan and English corpora were annotated by listing every occurrence of evidential markers and classifying them according to their evidential categories (direct perception, inference, hearsay, and subcategories), as well as their morphosyntactic characteristics (parts of speech, positions, and functions within the sentence).

Evidentiality in Tibetan and English

Evidentiality in Tibetan

Among the fully grammaticalized evidentials available in Lhasa Tibetan, inflectional copulas and verbal suffixes can encode direct perception and inference, while hearsay evidentiality is rendered by enclitics [START_REF] Tournadre | A typological sketch of evidential/epistemic categories in the Tibetic languages[END_REF]Author, 2014: 112-144). Examples (1),

(2), and (3) illustrate the expression of the three main evidential categories with the direct perception suffix -song, the inferential suffix -bzhag, and the hearsay enclitic -za:

(1) I also counted 'egophoric' forms as evidentials. Egophoricity is essentially a typical trait of Tibetic semantics, and refers to forms that are associated with the speaker and his or her sphere [START_REF] Tournadre | La déixis en tibétain: quelques faits remarquables[END_REF]Tournadre & Suzuki, in press: 319-324). In practice, they can only be used when the speaker taps into his or her direct experience, so I consider them to be a subcategory of direct perception. In ( 4), the speaker is referring to what she did yesterday, and her statement relies on her memory of the past events she has experienced. In (5), the speaker talks about his birth. He cannot access this type of information directly, which makes the use of an egophoric marker ungrammatical. In this case, only a factual marker or a factual marker associated with a hearsay enclitic is possible. This shows that egophoricity is incompatible with an indirect access to information, and justifies its categorization as a subtype of direct evidentiality.

Apart from fully grammatical evidentials, Tibetan can also refer to information sources by using lexical tools, such as perception verbs (mthong 'see', nyan 'hear', etc.), verbs of speaking (zer 'say', bshad 'tell', lab 'say', gsung 'say', etc.), or other constructions (mdog.kha.po 'seem', bzo.'dras 'look like', etc.). However, the evidential system of Tibetan is far more grammatical than lexical. The TSC contains 1,918 occurrences of evidential forms, and 1,435 of them are fully grammatical morphemes (verbal inflections and enclitics). Information sources are thus rendered with fully grammatical forms more than 75% of the time in the TSC.

Evidentiality in English

In Author ( 2022), I argue that the evidential system of English shows patent signs of grammaticalization. Several criteria can help us locate a form on the lexicon-grammar continuum, but there is an overall consensus that forms such as inflections and clitics are grammatical whereas basic verbs or nouns are lexical. In English, the category of auxiliaries is closed since only its members display what is commonly called the NICE properties [START_REF] Huddleston | Some theoretical issues in the description of the English verb[END_REF]. Auxiliaries are consequently considered grammatical. Forms such as must or should can encode inferential evidentiality, so I argue that they are fully grammatical evidentials. Apart from auxiliaries, other English evidentials may show partial signs of grammaticalization, such as the semi-auxiliary seem or the parenthetical I guess. However, they are not fully grammatical, and for this reason I treat them as (semi-)lexical evidentials. The most common evidentials in the CSC belong to several classes:

-auxiliaries: must -semi-auxiliaries: seem to, have to… -perception verbs: see, feel, look… -cognition verbs: guess, presume… -perception copulas: look, sound… -verbs of speaking: say, be like… -adverbs: apparently, presumably… I applied the same strict criteria to identify evidentials in Tibetan and in English. I thus didn't count as an evidential any form that does not encode a type of information source per se, but expresses another neighbouring semantic domain instead, such as epistemic modality:

(6) He had a freaking and awesome regent who may or may not have been his son. (LAC)

The auxiliary may differs from must because the latter always entails an inference in its epistemic use. As in (6), may can simply refer to speculations that are not necessarily due to the speaker's inferential access to information. Consequently, I do not consider may to be an evidential because it encodes an epistemic possibility and not a type of information source.

I also excluded certain cognition verbs because they do not refer to information sources but give a subjective tone to a statement:

(7) I eat it sometimes but I don't think it's good for you at all. (LAC)

The phrase 'I don't think' does not reveal whether the speaker bases her statement on direct perception, inference or hearsay, but suggests that she is not telling universal truths but rather sharing a personal opinion.

Phrases that did not express the speaker's information sources but that of another person were also excluded:

(8) But she was driving on there one night and she sort of saw a motorcyclist come up behind her and overtake her like boom and... (CSC)

A construction such as she saw + bare infinitive clause does not indicate how the speaker got to know what she is stating, so it cannot be counted as an evidential, while I saw + bare infinitive clause may be.

Finally, I only counted as evidentials forms that have scope over some propositional content, which excludes phrases such as ( 9):

(9) I heard him through the wall. (CSC)

Even though I heard + NP is related to the speaker's access to information, it is not an evidential specification on a propositional content but a simple report of a perceptual event.

The only fully grammatical evidentials that can be found in the CSC/LAC are 7 occurrences of must out of a total of 441 evidential forms. The expression of evidentiality in these corpora is thus almost entirely lexical or semi-lexical, since information sources are rendered by (semi-)lexical forms 98.5% of the time. This suggests that English barely uses fully grammaticalized evidentials.

Pragmatic consequences of two different evidential systems

Frequency

One of the most notable differences between the TSC and the CSC/LAC is that Tibetan uses explicit markers of information sources far more frequently than English. One of the reasons for this contrast is that evidentiality is integrated in the tense-aspect-mood inflections of Tibetan verbs while English speakers have to use specific lexical forms to specify their information sources. As [START_REF] Bybee | Cognitive processes in grammaticalization[END_REF] has observed, grammaticalizing forms see their frequency of use increase dramatically, which further explains the high frequency of fully grammaticalized Tibetan evidentials.

The data from the TSC and CSC/LAC reveal substantial differences depending on which evidential category is considered. The TSC contains 1,114 evidentials that encode the speaker's direct perception of the state of affairs, while there are only 63 such instances in the CSC/LAC. Altogether, the data from these corpora suggest that evidentiality is expressed 73,769 pmw in Tibetan, and 11,009 pmw in English in the same contexts. Tibetan speakers use an evidential once every 14 words in the TSC, and English speakers once every 91 words in the CSC/LAC.

This suggests that evidentials are used approximately 6.7 times more frequently in Tibetan than in English on average and under the same circumstances. From the perspective of speech time, there are 464 evidentials per hour in the TSC (i.e. once every 8 seconds), and 97 per hour in the CSC/LAC (i.e. once every 37 seconds). 3 Table 2 sums up these results: The data in the TSC and CSC/LAC show a dramatic contrast between the frequency of evidentials in Tibetan and in English. However, any generalization from this data must come with two caveats.

Firstly, the frequencies were estimated from corpora that were collected with the aim of eliciting evidentials, and consequently, the number of occurrences is certainly higher in these corpora than in random conversation. To assess this difference, one can, for example, compare the frequency of evidentials, such as apparently or I guess, in the CSC/LAC and in the spoken subsection of the COCA. The frequencies of these markers are presented in table 3: These results confirm that evidentials must indeed be more frequent in the CSC/LAC than in spoken English in general. However, it is not possible to check this trend for spoken Tibetan because large corpora of conversation are lacking.

Secondly, the data collected should not lead us to conclude that the number of evidentials in discourse parallels the cognitive processing of information sources when an utterance is interpreted. The context often allows a hearer to infer the source of the information underlying a claim. For example, when Tibetan speakers specified how their parents had met, they used many hearsay markers, which are thus functionally redundant, since the type of information source is quite obvious. Even though evidentials are less frequent in English, linguistic usage does not necessarily equate conceptual representation, since even using an evidential once can imply that a whole passage is based on the same information source.

Despite these caveats, the striking contrast between the frequency of evidentials in the TSC and the CSC/LAC confirms that the evidential systems of English and Tibetan are substantially different. It is no surprise that the degree of grammaticalization of the evidential domain impacts the frequency of its marking in a language, but this is the first study that I know of which can present quantitative data based on comparable corpora. The frequency of evidential marking in turn impacts the other dimensions that I will investigate.

Semantic schematicity

Even though English possesses numerous lexical and (semi-)lexical forms to refer to information sources, these tools are not the exact semantic equivalents of the most grammaticalized Tibetan evidentials. English evidentials tend to display more specific semantic features than Tibetan evidentials, which usually have a broader semantic spectrum, and thus fulfil a more schematic function.

This tendency corresponds to a general contrast between the generic meaning of grammatical forms and the more fine-grained semantics of the lexicon [START_REF] Slobin | The origins of grammaticizable notions: Beyond the individual mind[END_REF][START_REF] Talmy | Toward a cognitive semantics: Volume 1: Concept structuring systems[END_REF].

Grammatical forms can only refer to domains that are highly abstract, such as time, definiteness, or evidentiality, while very specific meanings, such as 'computer', 'shoe', or 'jealousy' are rendered with lexical words, and never with grammatical means. As linguistic forms grammaticalize, they typically desemanticize, and gradually cover a semantic space that is compatible with a broad variety of contexts [START_REF] Sweetser | Grammaticalization and semantic bleaching[END_REF][START_REF] Traugott | On the rise of epistemic meanings in English: An example of subjectification in semantic change[END_REF]Heine, 1993: 89). For example, the English auxiliary will saw its boulomaic meaning bleach to denote futurity, and similarly, the Tibetan morpheme song underwent a process of desemanticization from a lexical verb of motion to an inflection marking direct evidentiality [START_REF] Oisel | On the origin of the Lhasa Tibetan evidentials song and byung[END_REF].

Tibetan speakers do not have to provide as many details as English speakers when they specify their information sources, because the evidential system of their language is more grammatical. For example, there is no convenient English translation of the Tibetan direct perception morpheme -song: By using -song, the speaker indicates that he was there when the event took place, and that he remembers that the fish moved. However, he does not specify whether he actually saw, felt, or heard the fish move. The Tibetan direct perception suffix -song is indeed appropriate with any of the senses.

An inflection such as -song is usually left untranslated in English, but various perception verbs are available to express direct perception. However, using one of them will actually specify which sensory channel was involved. Examples ( 11) and ( 12) illustrate this point:

(11) A couple of days before that, I saw my mother put on deodorant. (CSC) (12) I even heard some people say, 'oh if-if you're pro-choice but with a cut-off point, then it's essentially pro-, like, well, it's pro-life but in disguise'. (CSC)

English does possess other tools to encode evidentiality, but these other forms will also tend to be more informative than fully grammaticalized evidential morphemes. For example, several phrases can denote that a statement relies on hearsay in English, such as they say, I was told, I've heard, or apparently. At first sight, each of these forms may seem to be an appropriate translation of Tibetan -za:

( However, each of the above potential translation of -za will contain more semantic features than the original. The Tibetan evidential only specifies that the speaker has learned about the content of the proposition verbally. 'Hearsay' evidentiality refers a broad category: the speaker may have been told about the situation, heard about it on the radio, or read it somewhere, etc.

In English, however, each potential translation will be semantically more specific. For example, they say specifies that more than one person has told the speaker. To avoid saying anything on who reported the information, one could use the passive form I was told, but it would still specify that the speaker has learned about it in a conversation. It could not refer to something overheard, or broadcast in the media. Using I've heard would typically denote that the speaker has acquired this information orally, and not from a written text. In addition, I've heard in English is mainly used when the source is vague, and would sound evasive if the speaker has a specific situation of communication in mind. Finally, apparently may sound like a generic alternative, but it entails that the speaker considers the information credible, whereas -za does not indicate whether the speaker believes it or not. It indeed sounds awkward to confirm or contradict a statement that is under the scope of apparently while it is possible with -za:

(14) Apparently it's a good idea to learn English… The different set of evidentials available in the two languages results in different discursive options. Overall, lexical evidential systems constrain speakers to specify more elements about the situation in which the information was acquired, because highly bleached evidential morphemes are not available. English speakers can thus either avoid specifying information sources or be more specific than Tibetan speakers.

Optionality

Optionality is another salient feature that is often mentioned to distinguish lexical and grammatical forms [START_REF] Lehmann | Revision of Thoughts on grammaticalization: A programmatic sketch, 1[END_REF][START_REF] Lehmann | Revision of Thoughts on grammaticalization: A programmatic sketch, 1[END_REF]: 123-128). From a diachronic perspective, a decrease in optionality, i.e. 'obligatorification', is a central mechanism of grammaticalization, or at least a frequent by-product (Heine & Kuteva 2007: 34). For example, as the Latin verb habere grammaticalized into a future tense inflection in Romance languages, it became an undeletable element attached to the verb stem and was incorporated into the conjugation paradigm.

Similarly, Tibetan evidential suffixes -gi.'dug/-song/-bzhag grammaticalized from optional coordinated or subordinating verbs, and are now only deletable in very specific contexts.

Obligatoriness used to be presented as a defining component of grammatical evidentiality [START_REF] Aikhenvald | Information source and evidentiality: What can we conclude?[END_REF]), but it is now generally accepted that many evidential inflections and clitics can be optional (Aikhenvald, ed., 2018: 10). Assessing optionality is more problematic than it seems, and will mainly depend on contexts. It is necessary to distinguish several linguistic levels: syntax, semantics, and pragmatics.

According to [START_REF] Crystal | A dictionary of linguistics and phonetics[END_REF][START_REF] Crystal | A dictionary of linguistics and phonetics[END_REF]: 329), an optional element is one 'that can be removed from a structure without that structure becoming ungrammatical'. It is indeed ungrammatical to delete the inflection of a verb in a main clause in Tibetan: The English translation of ( 16) does not include any evidential, but if the speaker wishes to specify that the statement is based on an inference like in the Tibetan sentence, whatever means the speaker could resort to will typically be deletable, as shown in ( 18) and ( 19).

(18) I can see that she's recovered well.

(19) She's recovered well.

However, syntactic optionality is not the only level to take into account when assessing how optional an evidential system is. Because evidential forms can be replaced by factual forms, it cannot be claimed that Tibetan speakers are obliged to refer to their information sources in every sentence they produce. Evidentiality is, for example, less obligatory than number in English. When using a countable noun in a sentence, one has to specify if it is singular or plural, because no neutral inflection is available in English. Because Tibetan possesses factual forms in the same paradigm as evidentials, evidentiality may be considered semantically optional in Tibetan.

A third dimension makes the picture even more complex: pragmatic obligatoriness. It may usually be possible to avoid mentioning information sources, but it is pragmatically awkward to never use any evidential, and this is more the case in Tibetan than in English. A certain pragmatic constraint inciting the use of evidentials despite the availability of factual markers might explain their high frequency. To illustrate this pragmatic dimension, one can compare how English and Tibetan speakers refer to their information sources in a similar context. For example, one question that was asked for the collection of the corpora was about the consultants' early childhood: 'could you tell a story that happened to you when you were less than 3 years old ?'. For those events that happened at a very early age, consultants relied mainly on what their families told them. All the Tibetan consultants (8/8) specified their information sources by using hearsay evidentials, while only one English consultant (1/8) mentioned that she based her statement on what she was told. The following example is a passage from the TSC where a Tibetan speaker talks about her early childhood and uses six hearsay markers:

( Example ( 21) can be compared to (22), where an English speaker talks about his early childhood, but does not use any evidential.

(22) My parents and me err went to Disneyland Florida when I was about one and a half… two. And err I, y'know, they thought I would be, like, interested in meeting all the characters and, y'know, going on the, like, baby rides whatever… and I was just there, like, playing with, like, the gates and the doors, like, anything, like, mechanical or, y'know, actually, like, fiddling around with all the, like, weird metal knobs and things and, like, just lying on the beach and annoying the children who were building sandcastles or, like, yeah, destroying people's sandcastles, so I was like two… yeah… then I decided I could speak American as well, which is possibly the most embarrassing part. My parents still mock me for that one.

(CSC)

Although stating that grammatical evidential systems are obligatory and lexical ones are optional is an oversimplification, the contrastive data from the TSC and the CSC/LAC thus suggest that English speakers can avoid the use of evidentials more easily, particularly from a pragmatic perspective.

Economy

Another salient feature characterizing grammatical evidentials is their apparent simplicity of use from a morpho-phonetic, syntactic, as well as cognitive perspective. Extensive psycholinguistic experiments are still needed to reach firm conclusions, but an overall comparison of the two systems suggests that expressing information sources requires less time and effort in Tibetan than in English for L1 speakers.

Tibetan evidentials often consist of one morpheme made up of one syllable, such as 'dug,gis, -song, -bzhag, -za, etc. Tibetan also possesses heavier morphemes, such as -gi.'dug (allomorph of -gis), or yod.pa.'dra, but its evidentials are, on average, undeniably more concise than most of the tools English uses to specify information sources: apparently, I imagine, it looks like, etc. To encode evidentiality, the average number of syllables necessary is 1.3 in the TSC (2,504 syllables for 1,918 evidentials) and 3.2 in the CSC/LAC (1,422 syllables for 441 evidentials). Expressing information sources thus seems to require 2.5 as many syllables on average in English as in Tibetan.

This tendency can be explained by a process of erosion generally associated with grammaticalization (Heine & Reh, 1984: 17-25). Grammaticalized forms tend to reduce phonetically, and diachronic data on Tibetan evidentials confirm this tendency. For example, the direct perception suffix -gi.'dug most probably comes from the construction V + gin + 'dug in Middle Tibetan, and is often reduced into -gis (/giɁ/) in contemporary Lhasa Tibetan: Stacking two Tibetan evidentials is an even more telling case of morpho-phonetic economy.

As hearsay evidentials appear in another paradigm than verb inflections, they can be combined with a direct or inferential morpheme. From a syntactic perspective, Tibetan evidentiality is also more economical than the English evidential system. Expressing information sources in English often requires constructions that make the sentence syntactically more complex, such as auxiliation or subordination. One can thus compare the syntactic structure of a sentence in Tibetan (Fig. 2) with the structure of an English translation that would maintain the evidential specification of the source language (Fig. 3): Thirdly, as several psycholinguistic studies have shown, lower frequency items usually take more time to be retrieved that higher frequency items [START_REF] Balota | The locus of word-frequency effects in the pronunciation task: Lexical access and/or production[END_REF][START_REF] Jescheniak | Word frequency effects in speech production: Retrieval of syntactic information and of phonological form[END_REF][START_REF] Kittredge | Where is the effect of frequency in word production? Insights from aphasic picture-naming errors[END_REF]. Because English resorts to numerous lexical items of various frequencies to specify information sources, it probably requires more effort for English L1 speakers to produce evidentials than for Tibetan L1 speakers, who use highly frequent forms more automatically.

In the TSC, the most frequent evidentials for each evidential category are 'dug for direct perception, bzo.'dras for inference, and -ze for hearsay. Their estimated frequencies are 15,962 pmw, 10,653 pmw, and 4,538 pmw, respectively. In the CSC/LAC, the most frequent evidentials for each evidential category are I remember + V-ing for direct perception, look (like) for inference, and say for hearsay. Their estimated frequencies are 502 pmw, 2,984 pmw, and 630 pmw, respectively. Overall, the data from the corpora suggest that English speakers encode evidentiality by choosing from a set of markers that have an average frequency of 4,098 pmw, while the average frequency of English evidentials is 345 pmw. When expressing evidentiality, Tibetan speakers thus draw from an inventory of forms that are on average 12 times more frequent than those available in English if one extrapolates from the data in the TSC and CSC/LAC.

To sum up, even though linguistic complexity is notoriously difficult to assess, since many parameters have to be taken into account, comparative data from the TSC and CSC/LAC confirm that Tibetan evidentials are on average less phonetically heavy, syntactically convoluted, and sporadic than English evidentials. This suggests that encoding information sources is significantly more economical in Tibetan than in English.

Information hierarchy

Boye & Harder (2012) argue that the determining factor characterizing the grammatical status of a form is its discursive secondariness. Tibetan evidentials are indeed typically more backgrounded than English evidentials in the information hierarchy of a sentence. The following tests corroborate this tendency.

First, it is pragmatically infelicitous for an evidential inflection to be the nuclear stress of a tone unit, as in ( 33): Except for metalinguistic emphasis, the nuclear stress is unlikely to fall on the evidential suffix -song in ( 33), but should fall on either 'di or lab. Most evidential equivalents in English are focusable. In (34), the underlined syllable is a potential nuclear stress.

(34) I heard him say that.

Then, if a Tibetan sentence that includes an evidential is negative, the proposition is negated, and not the information source, as in ( 35 Finally, a question that follows an utterance containing a grammatical evidential will not pertain to the information source but to the content of the proposition. One can compare ( 36) and ( 37): In (36), ga.'dra aks about the manner in which the statement was made, not about the speaker's information source. Conversely, in (37), how will most likely inquire about details on the speaker's information source.

The differences between grammatical and lexical evidentiality that were pointed out in 5.1, 5.2, 5.3, and 5.4 also participate in the backgrounded status of Tibetan evidentiality. Firstly, because evidentials are far more frequent in Tibetan than in English, they also tend to be less noticeable. As argued in [START_REF] Haiman | Ritualization and the development of language[END_REF] and [START_REF] Bybee | Cognitive processes in grammaticalization[END_REF], the routinized use of a linguistic form leads to a process of habituation, which makes it lose its salience. Just like an organism ceases to respond to repeated stimuli, the systematic use of evidentials in Tibetan probably weakens the attention the hearer will pay to them, whereas rarer, lexical forms tend to be more foregrounded. Secondly, we saw that English evidentials usually contain more details on the situation in which the speaker acquired the information. Because lexical evidentials tend to possess more semantic features, they also probably stand out more sharply than fully grammaticalized evidentials, whose semantic contributions are more generic and vague.

Thirdly, Tibetan evidentials are generally less optional than English evidentials. According to Grice's maxim of quantity [START_REF] Grice | Logic and conversation[END_REF], using an optional linguistic element implies that it is necessary for the conversation. This reinforces the foregroundedness of English evidentials since their greater optionality suggests that their contribution to the sentence is quite essential whereas obligatory evidentials can more easily go unnoticed. Finally, the morpho-phonetic profile of English evidentials also contribute to their sharper discursive salience. It seems fair to assume that stressed multisyllabic words or multi-word constructions are on average more noticeable than eroded grammatical morphemes.

The informational contrast between Tibetan and English evidentials reflects a general difference between a grammatical and a lexical rendering of a notion. Similar phenomena may be observed when comparing languages with a fully grammaticalized gender system and those which mainly resort to lexical items to express it. For example, because gender is less grammaticalized in English than in Spanish, saying 'a female cat' probably lays more emphasis on gender than simply using 'una gata'. Because extra lexical words are usually avoided unless they are essential to the message, it is probably more difficult to refer to gender in English without drawing attention to it, while gender is informationally unmarked in Spanish as it is a pervasive grammatical constraint. Likewise, the grammars of Tibetan and English do not offer the same discursive possibilities for speakers who wish to specify their information sources.

Using an evidential in Tibetan is the norm whereas using an evidential in English must be justified, and will consequently be more noticeable.

Conclusion

In this paper, I have investigated how languages with complex evidential paradigms and languages which mainly encode information sources lexically differ in their usage. This corpusbased analysis of Tibetan and English has revealed substantial pragmatic contrasts in the use of evidentials in conversation. The first striking difference is the frequency of evidentials, which occur 6.7 times more frequently in Tibetan. The evidential systems of Tibetan and English do not impose the same constraints on the speaker's discursive choices. Tibetan evidentials may be less optional than English evidentials, but expressing information sources in English requires the use of forms that are less generic, economical, and backgrounded.

Further research is necessary to reach firmer conclusions. The collection and annotation of larger corpora in Tibetan will allow us to measure the frequency and diversity of its evidential system more precisely, and would then make its comparison with the English system more accurate. Collecting corpora of conversations in languages with other evidential systems will also help us understand how typological differences may impact pragmatics. Lastly, the results of my corpus-based investigation would greatly benefit from psycholinguistic experiments.

Exploring frequency, semantic schematicity, optionality, economy and information hierarchy with various behavioural tasks will certainly provide us with valuable data for a better account of the interaction between evidentiality and cognition.

Fig. 1 .

 1 Fig. 1. Frequency of evidentials in Tibetan (TSC) and English (CSC/LAC) (per million words)

  moved from inside the plastic bag.' (TSC)

  FACT;COP =HSAY 'When I was little, I was very unruly… Compared to boys, I was unruly. That was famous. I would get up in the early morning, and play with the water in the sink. I would jump from the roof… I was always doing stupid things… I was very unruly. If my dad and my mum left me at home, I would hang a rope out of the window, and climb down… I would do that… When I was young, I was very unruly… And even compared to boys, I was unruly…' (TSC)

  recovered well.' (TSC) ≈ I see that she has recovered well.

Fig. 2 .

 2 Fig. 2. A syntactic representation of yag.po drag-bzhag

  that.' (TSC)

  The following two examples illustrate this point:

	(4)
	kha.par nang-la tshur blug-pa.yin
	phone	in-DAT CIS	pour-EGO;CPL
	'I downloaded them on my phone.' (TSC)
	(5)

a.ni rjes-la nga skye-pa.red and then-DAT I be.born-FACT;CPL 'And then I was born.' (TSC)

Table 1

 1 If the raw frequencies of these forms are normalized, it appears that direct perception is explicitly marked 42,846 times per million words (henceforth 'pmw') in Tibetan, and 1,579 pmw in English. There are 515 inferential markers in the TSC, and 293 in the CSC/LAC. This suggests that inferential evidentiality is expressed 19,808 pmw in Tibetan, and 7,298 pmw in English. Finally, there are 289 occurrences of hearsay markers in TSC, and only 85 in the CSC/LAC. This may indicate that Tibetan speakers resort to hearsay evidentials 11,115 pmw, while English speakers use them 2,132 pmw on average. Table1and figure 1 synthesize these results: Evidential categories and frequency of evidentials in Tibetan (TSC) and English (CSC/LAC)

		Tibetan (TSC)	English (CSC/LAC)	Frequency difference
		(pmw)	(pmw)	(n times more frequent in Tibetan)
	Direct perception	42,846	1,579	27.1
	Inference	19,808	7,298	2.7
	Hearsay	11,115	2,132	5.2

Table 2

 2 Overall frequency of evidentials in Tibetan (TSC) and English (CSC/LAC)

		Tibetan (TSC)	English (CSC/LAC)
	Per million words	73,769	11,009
	Per hour	464	97

Table 3

 3 Frequency of apparently and I guess in the CSC/LAC and in the COCA (pmw)

		CSC/LAC	COCA
			(spoken subsection)
	Apparently	426	98
	I guess	551	185

Table 4

 4 The semantic features of they say, I was told, I've heard, and apparently

	Evidential	Semantic features
	They say	+ hearsay, + multiple authors, (+ oral)
	I was told	+ hearsay, + conversation, + oral
	I've heard	+ hearsay, + oral, (+ vague source)
	Apparently + hearsay, + partial commitment

  Because evidentiality is a semantic domain, one should also investigate whether evidentials are semantically optional. The 'deletability test' indicates whether a morphological paradigm is obligatory, but does not tell us whether all members of a paradigm necessarily express a given notion. Although Tibetan evidential suffixes cannot be deleted, they are semantically replaceable by evidentially neutral forms available in the same paradigm. Factual markers do not specify how speakers accessed the information they are

	(20)
	yag.po drag-yod.red
	well	recover-FACT;INCPL
	'She's recovered well.'

sharing, but still appear in the same paradigm as evidentials. Example (

20

) is perfectly acceptable regardless of the speaker's information source:

(≈ 'I saw her recover', 'I can figure out she's recovered', OR 'I've heard she's recovered')

  The combined morphemes 'dug-ze, pronounced as only one syllable (/duɁs/), indicate that the speaker knows about the situation from someone who was him/herself a direct witness. The meaning can only be rendered in English with a long,

	(29)
	bu	de	yag.po 'dug	=ze
	child DEM nice	DIR;COP =HSAY
	'That boy is nice.' (TSC)
	≈ I've heard from someone who knows him that he is a nice boy.'
	convoluted expression:

These three main evidential categories can be further divided into other subtypes. For example, direct perception can be visual or involve other senses; an inference can be based on sensory cues or on logical reasoning; hearsay can refer to a private conversation or a widespread rumour, etc.

The average frequency per hour is given as a mere indication, since the average frequency per million words is scientifically more accurate.


Moncef Garouani
email: moncef.garouani@etu.univ-littoral.fr

Jamal Kharroubi
email: jamal.kharroubi@usmba.ac.ma

MAC : An open and free Moroccan Arabic corpus for sentiment analysis

Keywords: Sentiment analysis, Opinion mining, Moroccan dialect, Arabic, Data Mining, Machine learning

The proliferation of social media has allowed Internet users to post their views and opinions online. This generated a vast amount of raw data in informal ways. For many organizations and individuals, this data is vital for providing insight into future decisions. Preprocessed corpora are considered as the basic requirement for the development and evaluation of opinion mining (OM) systems. However, the vast majority of corpora intended for OM research are not large and free for the researchers' community. This lack of free and large OM corpora represents a major obstacle for promoting research on sentiment analysis systems, especially for rich and complex languages as the Moroccan Arabic (MA) one. To overcome this gap, this paper presents a new contribution to the MA resources. A free and large Moroccan Arabic corpus consisting of 18000 manually labeled tweets resulting in a lexicon-dictionary of 30000 words labeled as positive, negative and neutral. To the best of our knowledge, MAC (Moroccan Arabic Corpus) is the first open and largest MA corpus for sentiment analysis. It is pioneer by its size, its quality given by the consistency of the native annotators (IAA=0.9), and its accessibility to the research community. The MAC is benchmarked for forthcoming works through an exploratory data analysis carried out using the two-sentiment analysis approaches for polarity classification as well as language identification. In addition, the MAC corpus along with the necessary code to explore it have been released.

Introduction

With the worldwide spread use of social media platforms, opinion mining has become a useful and prominent technique to capture public opinions and views in different disciplines. OM or sentiment analysis (SA) refer to a computational process to automatically extract individuals' opinions, feelings, or attitudes towards particular events or issues [START_REF] Abdelli | Sentiment Analysis of Arabic Algerian Dialect Using a Supervised Method[END_REF][START_REF] Garouani | Sentiment Analysis of Moroccan Tweets Using Text Mining[END_REF]. SA has a vital function in real-life applications and decision-making processes in various domains for individuals and organisms [START_REF] Garouani | Sentiment Analysis of Moroccan Tweets Using Text Mining[END_REF].

Sentiment analysis is a subfield of Natural Language Processing (NLP) that has gained a strong interest during the last few years. However, the detection of Arabic sentiment polarity is a challenging task, due to limitations of data resources and the language complexity, particularly for its vernacular varieties [START_REF] Garouani | Sentiment Analysis of Moroccan Tweets Using Text Mining[END_REF]. It has many types and forms, including the Classical Arabic (CA),language found in the Holy Quran, Modern Standard Arabic (MSA) used in education, newspapers and formal speech, and Dialectal Arabic (DA), which is the informal everyday spoken language, used in chat rooms and social media platforms.

In 2021, Morocco reached 20 million social media users with an annual growth of 23% compared to 2019 (Statista1 ). However, very little research focuses on the Moroccan vernacular Arabic due to the lack of free and publicly available corpus and lexicon resources than for other Arabic dialects [START_REF] Garouani | Sentiment Analysis of Moroccan Tweets Using Text Mining[END_REF][START_REF] El Abdouli | Sentiment Analysis of Moroccan Tweets Using Naive Bayes Algorithm[END_REF]. For instance, the Levantine Arabic [START_REF] Mihi | MSTD: Moroccan Sentiment Twitter Dataset[END_REF], as has the Egyptian dialect have been heavily studied, however, resources used for one Arabic country cannot be applied to another. Thus, there is still a need for Arabic corpora, especially for DA [START_REF] El-Khair | 1.5 Billion Words Arabic Corpus[END_REF].

This research aims to fill this gap, by creating a MA benchmark corpus and a lexicon-dictionary for use in data mining. In this paper we focuse on Moroccan Arabic Sentiment Analysis and we provide solutions to one of the challenges that faces SA by creating the largest MA corpus and lexicon-dictionary. This resource is based on data extracted from Twitter. It also provides an evaluation of this corpus, further demonstrating its quality and applicability.

The remainder of this paper is organized as follows : Section II provides an overview of works related to Arabic data mining, the constituent dataset for different Maghrebian dialects, and points out their availability for the research community. The process of collecting and annotating the MAC is described in Section III, to report afterward in Section IV the benchmarking experimentations and results. Finally, conclusions are drawn in Section V.

Related work

Sentiment analysis approaches

The problem of Sentiment Analysis has been widely studied on the European languages and the Asian ones [el-garouaniSentimentAnalysisMoroccan2021]. The proposed solutions are largely dominated by the use of two typical analysis approaches : supervised (corpus-based) and unsupervised (lexicon-based) approach.

Corpus-based approach The Corpus-based approach is a data-driven approach that requires a large labelled data to train a classifier such as Support Vector Machine (SVM), Artificial Neural Networks (ANN), Naïve Bayes (NB), and K-Nearest Neighbor (KNN).

Lexicon based approach The Lexicon based approach makes use of the words and their corresponding polarities. In sentiment analysis, the term lexicon is a synonym for the word dictionary, however, rather than words and their definitions in dictionaries, lexicons in sentiment analysis contain the words along with their corresponding polarities [START_REF] Abdulla | Towards Improving the Lexicon-Based Approach for Arabic Sentiment Analysis[END_REF]. That is, every word is associated with its sentiment orientation. The lexicon could be created from existing dictionaries or from a corpus [START_REF] Ayyoub | Lexicon-Based Sentiment Analysis of Arabic Tweets[END_REF]. Table 1 provides a compact summary of recent works on SA for Arabic text. Since the focus of this work is on data resources, the following section survey the corpora produced by different research communities within the scope of work on sentiment analysis, with an emphasis on research conducted on the Arabic language (standard and vernacular) especially the Moroccan one.

Maghrebian corpora

The Maghrebi Arabic is a variety of vernacular Arabic spoken primarily in the Maghreb region (notably Morocco, Mauritania, Algeria, Libya and Tunisia). An increasing effort is being made to process Maghrebian dialects [START_REF] Mihi | MSTD: Moroccan Sentiment Twitter Dataset[END_REF]. In 2018, for sentiment polarity identification from newspaper comments, Rehab et al. presented SANA [START_REF] Rahab | SANA : Sentiment Analysis on Newspapers Comments in Algeria[END_REF]. An Algerian dataset of 178 comments annotated into positive, negative, and neutral categories. In their evaluation study, they found that the KNN classifier outperformed the SVM. Similarly, in [START_REF] Abdelli | Sentiment Analysis of Arabic Algerian Dialect Using a Supervised Method[END_REF], 10K Facebook comments were manually classified into positive and negative polarities, whilst the work in [START_REF] Guellil | SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis[END_REF] describes an automated technique for categorizing 8000 Algerian messages into positive and negative comments.

Mdhafar et al. presented TSAC [START_REF] Mdhaffar | Sentiment Analysis of Tunisian Dialects: Linguistic Ressources and Experiments[END_REF], a Tunisian corpus of 17K comments collected from the Facebook social media and manually annotated in positive and negative comments. Another automated process, described in [START_REF] Abdellaoui | Using Tweets and Emojis to Build TEAD: An Arabic Dataset for Sentiment Analysis[END_REF], gathered about 6 million tweets using the Twitter API, of which more than 170K were written in Maghrebi Arabic. However, the authors have tagged just 1000 tweets. Concerning Libyan Arabic, the authors of [START_REF] Alfared | A Topic-Based Twitter Sentiment Analysis Training Dataset for Libyan Dialect[END_REF] have recently put together a manually annotated corpus of 2938 tweets categorized as positive, negative and neutral.

Not long ago, a method to extract Moroccan tweets by geographical localization has been presented [START_REF] El Abdouli | Sentiment Analysis of Moroccan Tweets Using Naive Bayes Algorithm[END_REF]. Besides, [START_REF] Oussous | ASA: A Framework for Arabic Sentiment Analysis[END_REF] introduced ASA, a multi-domain corpus of 2000 Moroccan tweets tagged as positive and negative tweets. Likewise, [START_REF] Maghfour | Standard and Dialectal Arabic Text Classification for Sentiment Analysis[END_REF] gathered a dataset of approximately 10K positive and negative Facebook comments written in Moroccan and Modern Standard Arabic. Table 2 shows more details about some of the state-of-the-art Arabic corpora. As can be seen, compared to other languages, the Moroccan dialect has no large-scale free available corpora to carry out studies and benchmark new approaches. In addition, some of the public available ones provide no information about the annotation, which may limit their use. This paper aims to fill this gap by presenting the creation and annotation details of a large-scale Moroccan Arabic corpora and lexicon-dictionary. In addition, we will make it freely available to the research community.

Benchmark corpus

The constructed Benchmark provides a large-scale corpus spanning several domains, including sports, arts, politics, education, and society. The data collection, filtering, cleaning, and pre-processing steps are illustrated in Figure 1.

Data collection

To build the MAC corpus, we have developed a Python program based on the Twitter API2 for the extraction of data. This API provides access to Twitter data (tweets, users informations, etc.). Our target content was picked based on three methods of Twitter API data collection :

• Streaming API : that allows getting the tweets in real time. Selecting tweets in Arabic meeting Morocco as location requirement was performed. We managed to extract 8975 valid tweets from 23743 tweets collected. • User timeline API : that returns the most recent tweets posted by a specific user. In this stage, we used SocialBakers 3 to determine the most active Moroccan Twitter accounts. We managed to extract 5371 valid tweets from 10485 collected tweets from a list of 29 user timeline. • Search API : that retrieves a tweets that match a particular query. At this stage, we resorted to the Trendsmap4 to extract the hottest hashtags in Morocco. We have around 950 separate hashtag which are again used to collect tweets. We managed to extract 3654 valid tweets after filtering the Arabic tweets.

The final corpus consists of 18000 valid tweets based on 36114 tweets collected. 9750 were published by men and 7550 by women. Of 700 tweets could not be identified the gender of the author due to lack of information. Table 3 shows the distribution of tweets collected.

Data annotation

The collected tweets were tagged by two native speakers (ourselves). A first step of double labeling involving 2500 tweets was carried out. It allowed us to familiarize ourselves with the task of labeling. The rest of the tweets were tagged individually. We calculated the inter-annotator agreements on the 2500 duplicate tagged messages (IAA = 0.97). The tweets have been tagged according to the polarity (Positive, Negative, Neutral and Mixed) and language of the tweets (Standard Arabic, Dialectal Arabic). The labeling was done through a web application that we have developed to accomplish this task.

Data properties

The corpus has been categorized into four classes of sentiment, namely Positive, Negative, Neutral and Mixed (positive + negative), and two classes of languages used MSA and DA. The corpus characteristics are shown in Figure 2 and Table 4.

Lexicon construction

The construction of emotions lexicon is a very difficult task that conditions the success of the lexicon-based approach. The challenge arises from the complexity of the Arabic language and the large number of words to be taken into account. In addition, determining the polarity of many words can be very difficult for many reasons, such as the different meanings and connotations of each word depending on the context and cultural background of the person who publish the tweet. The table below shows an example where a word can have multiple meanings / polarities depending on the context :

ی Eng: Forward َ ّ َ َ Neutral
The constructed lexicon-dictionary in this study is created automatically from the annotated corpora. It consists of about 30.000 Moroccan Arabic term, where each word is assigned a polarity (positive, negative or neutral). Table 6 provides statistics about the constructed dictionary.

Experiments & Results

The SVM, Logistic Regression, CNN and LSTM classifier form the algorithms that we have chosen to conduct this benchmark study. In order to train the classifiers, a 5-fold stratified cross validation strategy was used.

We have proposed two tasks, the first is to identify the used language (MSA or DA) and the second centered on the analysis of feelings, given a tweet written in MSA or DA, this task consists of classifying it according to the feeling / emotion expressed by its author (positive, negative, neutral or mixed).

Task 1 : Language identification

Tables 7 shows the different scenarios settings that we have evaluated. The first column represents the used classifier name. The second column indicates the used features and whether a Stopwords filter was used (1) or removed (0). The third column shows the obtained accuracy. The best result by using the word embeddings representation is of 91.27%, obtained by using the LSTM classifier keeping the stop words, and 89.78% by removing them is acheived by the CNN.

Task 2 : Sentiment analysis

Table 8 shows the obtained results for the second task. The best result in terms of accuracy on the MSA corpus is 92.09% was obtained using the LSTM classifier. On the Dialectal corpus, the CNN reached an accuraccy score of 85.42% using the lexicon-based approach, while LSTM attained 93.24% on the whole corpus(AS+DM) using the supervised approach (corpus-based).

Conclusion

This study set out to fill the gaps in the literature by constituting the largest and freely available 5 benchmark corpus of Moroccan tweets created for ASA. This paper described in detail the creation and pre-processing of the corpus and lexicon, explained the annotation details that were adopted in creating the MAC, and described the features of the corpus, which consists of 18000 Moroccan tweets and a lexicon dictionnary of 30000 distinct words. A serie of experiments was applied on the MAC to offer benchmark results for forthcoming works. Furthermore, this dataset could be expanded to include more valuable texts coming from Facebook and/or YouTube.

Fig. 1 :

 1 Fig. 1: The flow chart of the proposed construction approach.

Fig. 2 :

 2 Fig. 2: Classes distribution.

Table 1 :

 1 List (sample) of recent works on sentiment analysis.

	Reference Language	Approach Dataset size	Performance
					Criteria	Result
	[7]	Jordanian	Lexical	900	Accuracy 86.89%
	[6]	Jordanian	Lexical	2000	Accuracy 70.05%
	[1]	Algerian	supervised	49864	Accuracy	86%
	[8]	Algerian	supervised	4000	F1-score	78%
	[9]	Moroccan	supervised	9901	F1-score	84.33%
	[10]	Moroccan	supervised	2000	Accuracy	93%
	[2]	Moroccan	supervised	13550	Accuracy 92.09%

Table 2 :

 2 Arabic corpora for sentiment analysis.

	Dataset	Size	Arabic	Classes	Source	Year Publicly
						Available
	[15]	10006	Egyptian	4	Twitter	2015
	[16]	17573	Saudi	3	Twitter	2017
	[17]	5400	Saudi	6	Twitter	2018
	[12]	17000	Tunisian	2	Facebook	2017
	[13]	6m	Tunisian	2	Twitter	2017
	[14]	2938	Lybian	3	Twitter	2019
	[11]	178	Algerian	3	Newspapers 2019
	[1]	49864	Algerian	2	Facebook	2019
	[3]	930	Moroccan	2	Twitter	2017
	[9]	10254	Moroccan	2	Facebook	2017
	[10]	2000	Moroccan	2	Twitter	2019
	[4]	12K	Moroccan	4	Twitter	2020

Table 3 :

 3 Statistics on valid tweets annotated.

	MSA	DA	Total
	9640	8360	18000

Table 4 :

 4 Details on valid tweets collected.

	Number of tweets	18000
	Number of retweets	4076
	Number of distinct users	2354
	Data collection period	01-Jan -27-Apr 2021

Table 5 :

 5 Statistics on valid tweets annotated.

	Tweet		Word	Polarity
	Ar:	ی
	Eng: You are in progress	ُ ّ َ َ	Positive
	Ar:

Table 6 :

 6 Statistics about the constructed dictionary.

	Positive	Negative	Neutral	Total
	10671	2057	17272	30000

Table 7 :

 7 Results of identification of the used language.

	Model	Features	Stop words	Accuracy
	LSTM	Word embeddings	0 1	91.27 89.23
	CNN	Word embeddings	0 1	89.78 89.16
	SVM	TF-IDF	0 1	89.13 86.30
	LR	TF-IDF	0 1	88.64 87.08

Table 8 :

 8 Evaluation results of the second task.

	Model	Approach		Performance
			AS	DM	AS+DM
	CNN	Corpus Lexicon	91.78 90.85	84.17 85.42	90.87 89.25
	LSTM	Corpus Lexicon	92.09 90.88	83.36 84.53	93.24 89.62
	SVM	Corpus Lexicon	84.75 82.04	67.80 74.14	88.05 78.11
	LR	Corpus Lexicon	82.23 81.08	65.78 71.77	79.88 77.96

https://www.statista.com/

https://developer.twitter.com/en/docs/twitter-api

https://www.socialbakers.com

https://www.trendsmap.com


Luidnel Maignan

Frédéric Gruau

Integer Gradient for Cellular Automata: Principle and Examples

When programming a spatial computing medium such as a cellular automaton, the hop count distance to some set of sources (particles) is an often used information. In particular, we consider the case where the sources themselves are moving. Due to the locality of communication, only an estimation of the distance can be made at each time step, and each location. When no assumption is made on the size of the medium, that distance takes its values in N, which is not desirable, because it does not lead to finite state. This paper shows how to use the modulo operation to project that set of N-fields into a finite set of Z/nZfields. Using the modulo stored at each site, we show that we are still able to compute the local differential of the original field, allowing to manipulate the former as a directional gradient. It allows us to evaluate the direction of the nearest source, provided the sources move at bounded speed, less than one site per time unit. This information can be used to solve several problems of spatial nature. In the particular case of cellular automata, we present two rules using the modulo representation of distance field: Voronoi Diagram and Convex Hull. The two rules applies for moving sources, although at the moment, the convex hull has been implemented only for static sources.

I. INTRODUCTION

Spatial computing considers a computing medium made of many elementary processing elements with local connections and homogeneously distributed in space. When programming the medium, a common ingredient is to evaluate the distance to some source objects. Using this information, it is possible to move an agent away from or towards the sources [START_REF] Coore | Botanical computing: a developmental approach to generating interconnect topologies on an amorphous computer[END_REF], compute the Voronoi Diagram [START_REF] Maignan | A 1D cellular automata that moves particles until regular spatial placement[END_REF] [START_REF] Maignan | Uniformisation de la répartition spatiale d'un ensemble de points par diagramme de voronoï: Implémentation sur automate cellulaire[END_REF], or the Convex Hull [START_REF] Adamatzky | Identification of Cellular Automata[END_REF] among many examples. In all of those examples, the actual value of the distances does not matter; only the differential of the distances is actually used.

Depending on the framework, various kind of rules can be used to compute the distances. A classical way to compute them is to diffuse a gradient of chemical, and use the chemical density as a distance information [START_REF] Coore | Botanical computing: a developmental approach to generating interconnect topologies on an amorphous computer[END_REF]. In this case, the distances take their values in R. In cases where the space can be described by a graph, the hop count distance can also be used. Between two nodes, it is defined as the number of edges of the shortest path connecting them. Then the distance is a value in N.

In this article, we consider a spatial computing medium described by a bounded degree graph of nodes which are processing elements operating synchronously, in parallel. The hop count distance is computed to the nearest source, at any location. Also, the distance is used in a way such that only its differential really matters. We call the distance field the values associated to each node at each time. Nodes can host a point source which can dynamically move from one node to a neighbor one. A distance field is such that, the distance stored in one node is an estimation of the distance to the nearest node hosting a source at that particular time. The slower the movement of sources is, the more precise the estimation becomes. When (and if) the sources stop moving, the estimated distances should converge to the exact distances values.

We show that, if the differential is the only information that is exploited from the distance field, it is possible to transform the original distance field defined on N by a field defined on finite state set producing exactly the same behavior. We choose the word output to describe this differential, because we organize the rules managing a processing element into several layers, where the layer responsible for computing the distance field outputs this differential to some higher level layer which is using it. We describe two cellular automata rules that only use the differential of the distance field. The first one is the Dynamic Voronoi Diagram of a set of moving sources, and the second is the Convex Hull of a set of static sources.

II. INFINITE DISTANCE FIELD WITH FINITE STATE

This section is organized as follows. We start off by giving two rules that produce N-valued distance fields with somewhat different properties. Then we underline the fact that distance fields are often used as directional gradients. We then define reasonable properties that needs to be satisfied in order to transform the N-distance fields into Z/nZ-distance fields for some bounded n, providing the way to produce exactly the same output from the new field.

A. Computation and use of the distance field

Before going into any details of the transformation of the N-distance field into a finite distance field, let us describe first how it is possible to locally compute the N-distance field. Considering a predicate source t (i) which is true if there is a source in the site i at time t, the distance field d is computed by the following rule:

d t+1 (i) = 0 if source t+1 (i) 1 + min{d t (j)} j∈N (i) otherwise.
(

This well-known rule [5][3][2] converges to a configuration where each node i of the considered graph has its d(i) equals to the distance to the nearest source. Using this information, an agent moving in the graph can decide to get closer or further from the sources. In [START_REF] Maignan | A 1D cellular automata that moves particles until regular spatial placement[END_REF], the case where the sources positions evolve in time is also considered. A slightly different version of that rule is used, which ensures that the distance field always indicates the direction to nearest source for any site at any time:

d t+1 (i) =      0 if source t+1 (i) 1 if ¬source t+1 (i) ∧ source t (i) 2 + min{d t (j)} j∈N (i) otherwise. (2)
In many important applications of this spatial gradient, it is often the case that only the difference between neighboring state values is required, not the actual absolute values of the states. Formally define:

δ t (i, j) = d t (j) -d t (i) for j ∈ N (i) (3)
Many applications depend just on δ, not on the values of d (except perhaps at the origin 0). The set of differences can be finite even when the set of absolute values is not. When this is the case, we will now show how to take advantage of this fact to quotient the state space into a finite set without affecting the outputs.

B. Properties of the distance field

The distance field can be seen as a layer that takes a set of sources as input and allows to compute the differential of the distance to the nearest sources as output. Whether this output is used in a dynamical or static way, some properties are required of the field in order to admit a finite state representation.

The most important property is that the difference between two neighbor sites must be bounded by some fixed constant ∆ at any time. As we have already defined δ t (i, j) in Eq. ( 3), the property can be written:

∀i∀j ∈ N (i) : δ t (i, j) ∈ [-∆, ∆] (4)
If it is not the case, then the set of outputted values is infinite, which prevent any finite state field to produce it.

The property (4) implies a bound on the speed of the sources in the dynamical case. Indeed, if the sources move one step each time for example, it moves as fast as the information in the field, so the sites can not update their values fast enough to preserve the ∆ bound. In fact, the ∆ bound is dependent on the speed of the sources when considering the two rules described above.

C. Transformation into a finite state field

If the property (4) is satisfied, then a simple modulo operator is enough to project the initial field d into a field f where the output is exactly the same:

f t (v) = d t (v) mod (2.∆ + 1). (5)
By this transformation, the N-distance field is transformed into a Z/nZ-distance field, with n = 2.∆ + 1. The former value is the size of the output set {-∆, . . . , 0, . . . , ∆}.

When applying the modulo operator, the global order on the values is lost, i.e. some values that were less than their neighbor's value have modulo value being greater. Because the definition of distance field depends on taking a minimum, we must correct for this explicitly. The neighbors who have these "mis-ordered values are:

N + (i) = {j ∈ N (i)|f (j) ≥ (f (i) -∆) mod n}
In order to correctly transform the rules (1) and ( 2), the values of N + (i) must be tested by the minimum operator before the others, because, if there are any, they correspond to the true minimal values in the original field. We obtain respectively:

f t+1 (i) =      0 if source t+1 (i); else: 1 + min{f t (j)} j∈N + (i) if N + (i) = ∅ 1 + min{f t (j)} j∈N (i) otherwise (1') f t+1 (i) =          0 if source t+1 (i); else: 1 if source t (i); else: 2 + min{f t (j)} j∈N + (i) if N + (i) = ∅ 2 + min{f t (j)} j∈N (i) otherwise (2')
where ∅ denotes the empty set. The output function is transformed into:

δ t (i, j) = (f (j) -n) -f (i) if j ∈ N + (i) f (j) -f (i) otherwise

III. VORONOI DIAGRAM AND CONVEX HULL

We present two examples in the context of cellular automata, where distance fields are used to solve non-trivial problems. Once the preceding method is applied, a finite state automaton can be derived.

A. Discrete Dynamic Voronoi Diagram

Voronoi Diagram of a set of sources can be defined as the set of sites that are equidistant to at least two sources. This is a very practical structure [START_REF] Aurenhammer | Voronoi diagramsa survey of a fundamental geometric data structure[END_REF] which makes a direct use of a distance field.

The computation of the Voronoi Diagram of a static set of sources is described in [START_REF] Adamatzky | Voronoi-like partition of lattice in cellular automata[END_REF], [START_REF]Fine-grain discrete Voronoi diagram algorithms in L 1 and L∞ norms[END_REF]. In this solution, a wave is sent by all the sources at the same time. When two waves meet, a Voronoi region boundary is materialized. This is possible because the synchronicity of the system is used to encode the distances in time, so that when two waves meet on a site, that site is equidistant to the two corresponding sources.

An interesting generalization is the dynamic computation of the Voronoi Diagram, under the motion of the sources.

We first designed a solution by sending waves periodically from all the moving sources. The detection of the Voronoi Diagram is done as described above, but materialized boundaries are removed after one period. Then the next waves re-materialize the boundaries at the correct location according to the (possibly) new positions of the sources. However, when the sources stop moving, they continue to send waves, which was unsatisfying. We were looking for a rule that could converge, i.e. when sources stop moving, the state of every site eventually fixes.

So we programmed a second solution by using the distance field to directly express the distances in space instead of in time. More precisely, by using the derivative of the distance field, equidistant points that compose the Voronoi Diagram can be seen as intersections of two circles with same radius, centered in two sources. Distance values in the circle are lower than the radius, while distances out of the circle are greater. Detection of the Voronoi Diagram is done by using the values of the distances of sites in the neighborhood of each site. Hence, almost all1 local configurations corresponding to a Voronoi Diagram boundary can be characterized by the following local predicate:

V t (i) = ∃j, k ∈ N (i) 2 , axis(j, i, k) ∧ d t (i) > max{d t (x)} x∈{j,k} , (6)
where axis(a, b, c) is a predicate that is true if the sites a, b, and c are along the same axis. Eq. ( 6) is valid no matter the number of dimensions of the space. Figure 1(a) shows two examples of circles with different radius, the resulting intersections, and the singular axis. This algorithm has been implemented as an hexagonal cellular automata rule. The distances are computed using rule (2), as its additional dynamic property is required, and Figure 1(b) illustrates the results. The rule also works fine when the sources move. Indeed, the rule is a simple detection of distances pattern, so the Voronoi Diagram boundary is updated as soon as the distances are; and when the sources stop moving long enough, the boundaries stop moving as soon as the distances converge.

Finally, the algorithm would work on other graphs, as it only relies on the notion of circles, which is constructed only with the the notion of distances. However, the errors due to the discrete nature of the space present in hexagonal grid case would be worse in a non-standard graph. Also, there is no obvious relation between a arbitrary graph and the euclidean space, so things like axis, for example, need to be redefined. The identification of well-behaving graphs could be of great interest.

B. Discrete Convex Hull

The discrete convex hull of a set of sources can be defined as the minimal connected component including all the sources and such that every shortest path between two points of the hull is also in the hull.

There exists a cellular automata rule that solves this problem for a connected set of sources [START_REF] Adamatzky | Identification of Cellular Automata[END_REF]. Its rule is defined for the Von Neumann neighborhood as:

c (i) = 1 if {c t (j)} j∈N (i) ≥ 4 c t (i) otherwise. (7)
The initial configuration encodes the source presence in a site i as c 0 (i) = 1, and the rule produces the convex hull according to our definition only if we consider the Euclidean length of the paths as distances. To our knowledge, there also exist algorithms that work on sets of non-connected sources, but all of them make some assumption of a previous knowledge about an upper-bound on the distance between the sources [START_REF] Jarvis | On the identification of the convex hull of a finite set of points in the plane[END_REF], [START_REF] Preparata | Convex hulls of finite sets of points in two and three dimensions[END_REF], [START_REF] Preparata | An optimal real-time algorithm for planar convex hulls[END_REF].

We will sketch here an algorithm that computes the convex hull without any previous knowledge. Indeed, as the definition of the convex hull involves shortest paths, we will see that it can be constructed from distance fields, which are the distances to the nearest source, i.e. the length of the shortest paths to the set of sources. As this result has not been published yet, only the insights will be given.

Our algorithm consists of the parallel composition of three stages:

1) Detection of middle points 2) Propagation to neighbors of lower distance value 3) Convexification The two first stages alone connect arbitrarily distant sources without adding any point outside of the convex hull. As the connectivity problem is solved, using a rule related to Eq. ( 7) as third stage produces the convex hull. Let us define and describe the three stages more carefully:

1) Middle points: "Middle points" are defined as the points on a shortest path between two sources, and equidistant to them. Since they lie along a shortest path between two points of the convex hull, they are in.

When two sources are sufficiently close compared to others sources, their middle points can be detected by only using the distance field from the set of sources. Indeed, middle points are the intersection of two tangent circles centered on the two sources and having the same radius. Figure 2 shows that relying of the same property of the circles used previously to define Eq. ( 6), the middle points can be detected using two singular axis. Thus, the rule is related to the following local predicate:

M t (i) = ∃j, k, l, m ∈ N (i) 4 , axis(j, i, k) ∧ d t (i) > max{d t (x)} x∈{j,k} ∧ axis(l, i, m) ∧ d t (i) < min{d t (x)} x∈{l,m} ,
2) Propagation and Delaunay-like Structure: During the propagation stage, the distant sources get interconnected. When taking two sources into account, the propagation draws every shortest paths from one source to the other. All these paths go through the middle points, and those middle points have the maximal distance value. Hence, it is enough to progress backwards from the middle points by detecting points that have a lower-valued neighbor:

P t (i) = ∃j ∈ N (i), c t (j) = 1 ∧ d t (j) > d t (i)
This makes the middle points propagate towards its two corresponding sources without adding points not belonging to the convex hull. In fact, going from a value to a lower value corresponds always to a shortest path from each site to its nearest source. The result is a connected set of sites connecting closer sources in a Delaunay-like fashion.

3) Convexifying Rule: The two previous stages transform a non-connected set of sources into a connected one by adding sites that lie in the convex hull. The last thing to do is to adapt the predicate used in the rule [START_REF] Adamatzky | Voronoi-like partition of lattice in cellular automata[END_REF], that is able to transform any connected set into a convex one, for the hexagonal case with hop count distance:

C t+1 (i) = {c t (j)} j∈N (i) ≥ 3
Now that all the stages are defined, let us define their parallel composition:

c t+1 (i) = 1 if M t (i) ∨ P t (i) ∨ C t (i) c t (i) otherwise.
Starting from a configuration where only the sites i containing a source are such that c 0 (i) = 1, this rule constructs the convex Thanks to the distance field modulo representation, this algorithm also requires only a finite number of state, as one can check that every defined predicates can be rewritten in order to only use differences. Figure 3 shows an execution trajectory where the three stages have been applied one by one, and three snapshots of the execution trajectory of the parallel composition of the three stages.

IV. CONCLUSION

In this article, we shown how to transform an unbounded distance field into a bounded-valued field. We show that this is possible only is the differences between adjacent sites is bounded, and we gives the relation that link that bound and the number of state of the transformed field. In spite of the fact that every thing is done only for the distance field, the described transformation may be usable for other integer fields satisfying the bounded difference requirement. We have also describes two algorithms using the intuitive language of integers: the Dynamic Voronoi Diagram and the Convex Hull. For both examples, it is clear that the distance is only used for its differential, allowing the transformation to be used in order to obtain cellular automata rules. Those algorithms have been programmed and tested in the case of synchronous cellular automata, using a square and hexagonal lattices. Future work includes expending this result to quasi regular architectures and quasi synchronous update, such as Amorphous Computers [START_REF] Abelson | Amorphous computing[END_REF].

Fig. 1 .

 1 Fig. 1. (a) For every point of the Voronoi Diagram, there exists a singular axis such that the distance field is a local maximum (b) Result of the computation of the Voronoi Diagram on an hexagonal grid

Fig. 2 .

 2 Fig. 2.Detection of middle points. The two circles are tangent, they correspond to all points that have the same distance as the middle point. The two axis are the maximum axis (inf-equal-inf) and the minimum axis (sup-equal-sup).

Fig. 3 .

 3 Fig. 3. (a) Middles detection (b) Delaunay-like structure (c) Convex Hull (d,e,f) intermediate configurations of the parallel composition of the three

Almost all, because, the discrete nature of the space requires some minor arrangement.

ACKNOWLEDGMENT

We acknowledge Andrew Adamatzky who pointed us to the Convex Hull problem and provide his knowledge on existing results and challenges on the subject, Christine Eisenbeis for her advices, and Sonia Dahdouh for her careful support, proofreading and advice. We would like to thank the reviewers of the article also, as they greatly contribute to improve its quality by their comments, and Daniel Yamins for his corrections and suggestions. We acknowledge support from EPRC grant EP/F003811/1 on general purpose spatial computation.