Discourse Markers as the Classificatory Factors of Speech Acts (2022)

Abstract: “Since the debut of the speech act theory, the classification standards of speech acts have been in dispute. Traditional abstract taxonomies seem insufficient to meet the needs of artificial intelligence for identifying and even understanding speech acts. To facilitate the automatic identification of the communicative intentions in human dialogs, scholars have tried some data-driven methods based on speech-act annotated corpora. However, few studies have objectively evaluated those classification schemes. In this regard, the current study applied the frequencies of the eleven discourse markers (oh, well, and, but, or, so, because, now, then, I mean, and you know) proposed by Schiffrin (1987) to investigate whether they can be effective indicators of speech act variations. The results showed that the five speech acts of Agreement can be well classified in terms of their functions by the frequencies of discourse markers. Moreover, it was found that the discourse markers well and oh are rather efficacious in differentiating distinct speech acts. This paper indicates that quantitative indexes can reflect the characteristics of human speech acts, and more objective and data-based classification schemes might be achieved based on these metrics.”

## discourse markers and the (dis)agreement continuum a discourse marker (dm) is a word or phrase that people often use in the process of communication, and its main function is to coordinate and organize discourse to ensure the smooth flow of conversation. in addition, as a carrier of pragmatic information, it usually reflects speakers' mental states and communicative intentions, thus facilitating pragmatic inference (furkó, 2020). in this regard, @xcite defined dms as "linguistically encoded clues which signal the speaker's potential communicative intentions." although scholars have never reached a consensus on the definition of dms, no one would doubt their diverse discursive functions and the capability to transmit communicative intentions. when analyzing the functions of dms, scholars also differ considerably in terms of their frameworks and research paradigms. @xcite distinguished dms from a semantic perspective: a dm either possesses a semantic meaning, which is interpreted in a particular context with some connection to its form (e.g., and and i mean); or it does not contain any semantic information (e.g., well and oh). however, @xcite pointed out that although some dms contain rich semantic information, there are particular contexts in which the communicative intention it conveys is not related to the semantic information it carries. for example, in some cases, the dm and can be used as a discourse continuative, filler word, and buffer term, etc. some scholars analyzed the range of functions through the functional-cognitive approach, which shows that dms have a specific rather than a completely arbitrary range of functions @xcite . @xcite also expressed support for the non-arbitrary nature of dm functions. she explicated this view in terms of the correspondence between form and function and argued that there are two probabilistically similar possibilities for the form-function correspondence, one in which a form corresponds to multiple functions and the other in which a function corresponds to multiple forms. she further claimed that these two possible relationships do not indicate the syntactic arbitrariness but are characterized by unpredictability since the same form may evolve to express many innovative meanings. in this sense, functionalists argue that the universality of dm forms (as opposed to the uniformity of forms) is functionally driven. the above investigations of dm functions have helped us to gain a deep and broad understanding of dms' nature and their functional orientations in various contexts. however, as @xcite mentioned, there is a great deal of uncertainty in dms' functions, and even those with a relatively fixed semantic meaning may produce new and rare uses in some contexts. in addition, the one form -many functions and one function -many forms nature of dms, as well as the innovative nature of their functions, also make their functions perform in a variety of ways. thus, it is difficult to assess all the functions of dms through an in-depth analysis of the discourse material one by one (the workload is too large). if we want to characterize all aspects of certain dms and explore the patterns of these linguistic units full of uncertainties and probabilities, it is better to apply an approach that is suitable for approximating all the features possessed by the dms. another consideration in employing this approach is that human communicative intentions are themselves fraught with probabilities and uncertainties. as pointed out by the speech act theory, there is not always a clear correspondence between the words people express and their functions, and speech acts are also characteristic of one form -many functions and one function -many forms as mentioned by @xcite . a more extreme example, such as kennst du das land wo die zitronen blühen? (knowest thou the land where the lemon trees bloom?), can even express the communicative intention "i am a german soldier" @xcite . by the same token, the various dms proposed by previous authors, such as the eleven dms by @xcite (oh, well, and, but, or, so, because, now, then, i mean, and you know), may occur in various speech acts depending on the specific speech context. to address the function of dms and the probability and uncertainty of human communicative intentions, the present paper tries to introduce some basic probabilistic and statistical methods, such as the hierarchical cluster analysis (hca), to quantitatively analyze the dms contained in specific communicative intentions. our aim is to examine whether certain indicators of dm (e.g., their percentage of frequency of occurrence in different speech acts) can effectively distinguish the communicative functions embodied in differing speech acts to propose a new research methodology for dm-related studies. in the current study, the frequency of different dms in differing speech acts was investigated as a possible defining feature for the distinction of communicative intentions. the reason for doing so is that dms carry diverse pragmatic and contextual information @xcite . in this regard, the frequency of dms may reflect the pragmatic characteristics of different speech acts, which may help us better explore the patterns of human communicative intentions. since we want to examine whether the frequency of dms can effectively distinguish different speech acts, these dms should first be able to reflect the differences between speech acts that differ significantly, e.g., agreement and disagreement, thanks and apology, etc. next, we may examine whether it can reflect the slight differences between similar speech acts. therefore, in the current paper, we applied the continuum of (dis)agreement (accept, partially accept, hedge, partially reject, and reject) as the object of study to explore whether the frequency distribution of dms can accurately capture the nuanced differences in speech acts. when analyzing the agreement-disagreement continuum, scholars have mostly focused on the perception of agreement-and disagreement-like speech acts by people in specific types of discourses. for example, @xcite found that strong disagreement is easier to declare in writing than face to face after examining the written letters by biochemists. when investigating the arguments of mentally disabled people, @xcite study showed that regarding conflict resolution as the primary goal of arguments detracts from the true nature of verbal conflicts -they reflect a social continuum of agreement and disagreement @xcite . @xcite compared dyadic discussions following initial agreement and disagreement and found that disagreement was more competitive, characterized by high rates of verbalization, increased numbers of turns, more frequent interruptions, and reduced back channels. ## results and discussions in this paper, the dm system (oh, well, and, but, or, so, because, now, then, i mean, and you know) proposed by @xcite was employed to explore whether the frequencies of dms can reflect the affinity relationship between different speech acts. this system, containing commonly occurring dms and widely accepted by the academic community, can capture how the diverse dms with distinctive functions demonstrate the similarities and peculiarities among different communicative intentions. as mentioned in section 2, the current study analyzed the five speech acts in the swda that express agreement or disagreement because they present a typical continuum, which facilitates a more detailed examination of the results of data analysis. the original text files of the five speech acts were firstly compiled. the five speech acts of agreement contain altogether 24,816 words, among which agree/accept has 19,942 words, maybe/accept-part 528 words, hedge 2,703 words, dispreferred answers 1,772 words, and reject 942 words). next, we applied antconc 4.0.5 @xcite to automatically get the total word count in the five speech acts, in which the frequency data of the eleven selected words/phrases proposed by @xcite were extracted. since the automatic process could not distinguish between the 11 words/phrases as dms and other cases, the authors manually checked the automatically collected data to obtain the exact dm frequencies for follow-up analyses. it should be noted here that the raw number of dm frequencies may affect the results of the statistical analysis due to the large variation in the total number of words in each speech act. in this regard, this paper calculated the percentages of each dm's frequency relative to the total word number to standardize the data. when converting the numbers to percentages, the authors distinguished two different kinds of c c l 2 0 2 2 dms: one for single words (unigram), such as oh, well, etc., and the other for two consecutive words (bigram), i mean and you know. for the former types of dms, we counted the percentages of dm frequencies relative to those of all unigrams in each speech act; for the latter, we calculated those of all bigrams, with the aim of making the standard uniform. after collation and calculation, the frequency data of the eleven dms proposed by shiffrin (1987) under each speech act were obtained, as shown in as can be seen from the following excerpts from the swda further illustrate the differences between agreement and disagreement as well as those between direct and indirect speech acts. a. dispreferred answers 1) well, i, i think, uh, my background is probably what absolutely turned me off with sixty minutes. from the utterances containing well in the speech act of dispreferred answers, we can see that well mainly serves to provide a buffer for the subsequent words. in addition, since the speaker wants to express opposition to the words spoken by the hearer without completely opposing them, he or she tends to use the strategy of repetition (e.g., the repetition of i in a. 1) and a. 3)) or continue to apply other dms as filler words to further moderate the illocutionary force of the speech act of opposition (e.g., you know in a. 4)). this phenomenon shows that people would frequently resort to the buffer dm well along with other means to minimize the force of opposition they are expressing. b. reject 1) well, i don't think you can mail thing, guns through the mail. when expressing direct opposition to another speaker's opinions, the frequency of well is also higher due to the principle of politeness and the consideration of face-saving strategy. although reject and agree/accept are both direct speech acts, the use of buffer words like well in direct disagreement is still significantly higher than that in direct agreement (reject: 0.0658 > agree/accept: 0.0117). c. maybe/accept-part 1) well, even if it's not technical. if it's, uh, some social thing or whatever. it doesn't matter. d. hedge 1) well, uh, it's funny, when i tried, to make the call the other days, c c l 2 0 2 2 e. agree/accept 1) oh, well yeah. among the three speech acts concerning agreement (agree/accept, maybe/accept-part, and hedge), the use of well is more convergent, serving as a simple tone buffer, and does not involve a strategy of face protection for the other interlocutor. according to previous studies on well, it is often employed as a delay device and a pragmatic marker of insufficiency, indicating the problems with the content of the current or the previous utterances, or as a face-threat mitigator, showing the conflicts in the interpersonal level @xcite . although well has a relatively fixed spectrum of discourse functions, its frequency of occurrence varies across discourses expressing different communicative intentions, depending on the specific context and the nature of probability within speakers' language use. therefore, to accurately capture how the frequency of well in different speech acts reflects their affinities, it is best to apply a more suitable method to study these probabilistic linguistic units. moreover, from the above analysis, well is a dm that can effectively distinguish between agreement and disagreement; however, people cannot merely use well when expressing these communicative functions; dms such as you know and and also frequently occur in these speech acts. in order to comprehensively and systematically grasp how the frequency of dms reflects the differences of each speech act, we included in the present study a more comprehensive dm system (that proposed by schiffrin). meanwhile, to avoid the overwhelming workload caused by manual qualitative analysis, we adopted established statistical methods to grasp the characteristics embodied in dms accurately. the factoextra and cluster packages in r were applied to perform an hca on the data in from the data in in summary, from the above analysis, it can be concluded that by employing a method that can accurately grasp the statistical patterns of linguistic units, we may be able to better capture the tendency of each speech act in using dms and establish the connection between the two important constructions (speech acts and dms) with the support from real data. this approach can complement well-developed qualitative analyses of dms, provide more comprehensive and theoretically supported results (e.g., the dm classification system proposed by schiffrin), and introduce the advantages of quantitative analysis (big data, objectivity, and accuracy) into the research related to pragmatics and discourse analysis. ## conclusions and implications in this study, we adopted a quantitative approach to analyze whether dms, the discourse units that possess discursive and pragmatic information, can effectively distinguish the speech acts of different communicative functions. after calculating the frequencies of the 11 dms proposed in @xcite , we 0 for all the clustering results using different methods and distance metrics, see appendix a.