From Diachronic to Contextual Lexical Semantic Change: Introducing Semantic Difference Keywords ( SDK s) for Discourse Studies (2023)

Abstract: This paper introduces the concept of Semantic Difference Keywords (SDKs). We define SDKs as keywords selected because of a comparatively high semantic difference between their use in two or more corpora. They are extracted by applying methods developed to identify diachronic Lexical Semantic Change. Like statistical keywords, most commonly used in quantitative discourse studies, SDKs capture the distinctiveness of a target corpus. However, they do not do so because they are used significantly more often or more consistently, but because they are used significantly differently. The case study presented in this paper shows that SDKs are successful in identifying concepts which are contested, i.e., sites of “semantic struggles” (CITATION). SDKs are therefore a useful contribution to (computational) discourse studies and text-based Digital Humanities more broadly.

## introduction in discourse studies, a keyword is a central concept to the comparative study of corpora. however, the identification of such keywords is most often predetermined by the researcher, or, in the case of corpus linguistics studies, by statistical measures based on frequency and/or dispersion. scholars have wondered how to identify keywords which are sites of "semantic struggles", i.e., which are at the centre of societal controversies and whose meaning is therefore contested @xcite . this paper proposes the concept of semantic difference keywords (sdks), defined as words or multi-word expressions (mwes) whose semantic difference between two or more corpora is comparatively large. sdks are extracted with methods developed for the study of diachronic lexical semantic change (lsc). this novel application of such methods is relevant to computational and digital humanities. as a case study, the discourse from latin american guerrilla movements from the cuban revolution onward was investigated. more specifically, the words whose meaning in the discourse issued by the ezln (zapatista army of national liberation) most differs from their meaning in discourses issued by the other movements in the corpus were studied by training a word2vec model where two different embeddings were learned for candidate sdks: one representing their use in the ezln corpus, and one representing their use in the rest of the corpus. this analysis highlights that this concept shows promises to identify words which are sites of contestation within a specific discourse. it also underlines that high semantic difference can be explained by a variety of factors and that their relevance is therefore dependant on the initial research question. stylistic markers, polysemy, context-dependant lexicon and ideological differences can all lead to variance in the context where words are being used by a specific group. ## defining semantic difference keywords sdks are terms whose meaning differs substantially between two corpora. otherwise stated, they are the words for which the semantic difference between their manifestation in one corpus and another is largest. in analogy with frequency or dispersionbased keywords, sdks capture the distinctiveness of a target corpus, not because they are used significantly more often or more consistently, but because they are used significantly differently. like frequency and dispersion-based keywords, they highlight the locations where the language of the two corpora differs at the lexical level. however, words which have similar relative frequencies and dispersions in two corpora, by definition, will not be selected as key, even if they are used in largely different ways, and therefore hold clues to fundamental differences in language use between the two corpora @xcite . in corpus linguistics, collocations are used to contrast how a word has different meanings or connotations in different contexts, but the words whose collocations are investigated are selected either because of underlying research questions, or according to frequency or statistical keyness criteria. in addition, they do not allow to measure how stable the meaning of the word under investigation is between the two corpora. the concept of sdk is therefore useful to automatically extract words or phrases whose meaning is most unstable across two or more corpora. not only can they contribute to identifying terms around which sociopolitical debates take place, but, like quantitative keywords, they could be leveraged for literary analysis, stylistic studies, authorship attribution, etc. ## case study as a case study, the discourse of latin american leftist armed movements from the cuban revolution onward is investigated. the language of latin american guerrilla discourse is relatively repetitive and heavily relies on fixed expressions and clichés. however, it has been argued that the ezln (zapatista army of national liberation), active from 1994 until today, offered a renovation of revolutionary leftist language in latin america @xcite . identifying sdks by comparing the ezln corpus and a comparison corpus of texts written by other latin american guerrilla movements from 1953 onward contributes to assess the ways in which this renovation takes place. ## discussion and future work the method is successful in pointing to words which are used differently in different corpora. however, for the sake of illustrating the concept of sdks, this pilot study relied on a single model and did not address potential robustness issues linked to the variability of word embeddings. for a fullyfledged analysis of the corpus, additional steps will be undertaken to increase reliability. first, im-plementing recommendations proposed by scholars who investigated the instability of word2vec models @xcite , especially those learned from comparatively small amount of data, will contribute to mitigate this issue. @xcite demonstrated that word embeddings are sensitive to small variations in the source documents, including their position in the corpora, suggesting that they are not trustworthy to study word associations. they recommend to average distance calculations over multiple bootstrap samples instead of relying on a single model. in addition, finetuning an existing model trained on a larger corpus instead of training a new model from scratch has proven to be a useful measure @xcite . second, the influence of the algorithm, hyperparameters, word frequencies and length difference between sub-corpora on the results should be investigated. to truly assess performance and validate results, the creation of ground-truth datasets for such tasks would be valuable, whether via the annotation or existing data or the creation of simulated data @xcite . see @xcite for details on the creation of a gold standard for the evolution of meanings of political concepts. as mentioned above, this pilot study aimed at illustrating the concept of sdks. however, by limiting the contextual referencing to the ezln corpus, the power of the methodology is limited. in future works, potential sdks will be referenced for all movements (frequency permitting) and divided into three periods informed by historical research of latin american leftist guerrilla movements (wickham-crowley, 2014). some movements have been active for several decades and significantly evolved over time. this more granular referencing will be used to identify ideological clusters as well as patterns of continuity and rupture in the discourse of insurgency in latin america @xcite . from a methodological viewpoint, by calculating all pairwise semantic similarities for potential sdks, we will be able to extract keywords which are most susceptible to semantic variability across the board, rather than focusing on one movement. in addition, when focusing on one movement, it will be interesting to look at words whose pairwise distances is abnormally large in comparison to the pairwise distances involving the other movements. beyond this specific adaptation of lsc metholologies, relying on contextualised instead of static embeddings to investigate semantic difference (see @xcite ; montanelli and periti (2023)) would be productive for this area of research, since it would allow for the assessment of the stability of word meaning within one (sub-)corpus as well as across different corpora. for instance, examining the variance within different sub-corpora would be useful to track patterns of influence and cross-fertilisation between different social groups. ## conclusions this paper introduced the concept of sdks, i.e., keywords or key terms which are used most distinctively between two or more corpora. this concept is useful for the field of discourse studies, where researchers are interested in the ways in which terms are leveraged for differing rhetorical purposes by different groups. the extraction of sdks bypasses the need for a predetermined shortlist of keywords. nevertheless, the reason behind semantic difference cannot be assumed and close reading is necessary to interpret results. in addition, researchers in the humanities and social sciences have to be wary of the potential instability or word embeddings @xcite . implementing recommended mitigating measures and reporting on variability metrics is key @xcite . ultimately, for this avenue of research to grow, the creation of more ground-truth datasets would be helpful. finally, like @xcite , this paper wishes to argue that methods developed for the identification of lsc can productively be used for synchronic semantic difference in discourse studies as they have unique capabilities to extract language patterns which would be difficult to decipher with other quantitative or qualitative discourse studies methods.