Topic Models and Word Embeddings for Ideological Analysis: A Case Study in Neoliberal Discourse

Mandenaki, Katerina; Sotirakou, Catherine; Mourlas, Constantinos; Moschonas, Spiros A.

doi:10.18848/2327-7882/cgp/v21i01/37-58

Cited by 2 publications

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“…See Wiedemann and Fedtke (2022) for a relevant survey of the topic. Such studies usually focus on one corpus (see, for instance Mandenaki et al (2022) and Durrheim et al (2023)). When the study is comparative, it usually investigates diachronic discourse change.…”

Section: Word Embeddings and Discourse Studiesmentioning

confidence: 99%

Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change

2023

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Welcome to the 4th International Workshop on Computational Approaches to Historical Language Change (LChange'23) co-located with EMNLP 2023. LChange is held on December 6th, 2023, as a hybrid event with participation possible both virtually and on-site in Singapore.Characterizing the time-varying nature of language will have broad implications and applications in multiple fields including linguistics, artificial intelligence, digital humanities, computational cognitive and social sciences. In this workshop, we bring together the world's pioneers and experts in computational approaches to historical language change with a focus on digital text corpora. In doing so, this workshop carries out the triple goals of disseminating state-of-the-art research on diachronic modeling of language change, fostering cross-disciplinary collaborations, and exploring the fundamental theoretical and methodological challenges in this growing niche of computational linguistic research.In response to the call, we received 28 submissions. Each of them was carefully evaluated by at least two members of the Program Committee, whom we believed to be most appropriate for each paper. Based on the reviewers' feedback we accepted 17 full and short papers as oral or poster presentations. We had two distinguished keynote presentations: the first by Gemma Boleda (Research Professor in the Department of Translation and Language Sciences of the Universitat Pompeu Fabra, Spain) who presented a talk entitled "What does semantic change have to do with Hello Kitty? Referring as the source of change", and the second by Mario Giulianelli (a postdoctoral fellow at ETH Zurich) with the talk "Neural language models for word usage representation and analysis". Finally, we invited five EMNLP'23 Findings papers to be presented as posters, which are not included in the workshop proceedings.To further support the community, we offered five student scholarships to cover registration fees. We also offered mentoring for four young researchers on their research topic in the field of language change, either during the workshop or virtually.We hope that you will find the workshop papers insightful and inspiring. We would like to thank the keynote speakers for their stimulating talks, the authors of all papers for their interesting contributions, and the members of the Program Committee for their insightful reviews. Our special thanks go to the emergency reviewers who stepped in to provide their expertise. We also express our gratitude to the EMNLP 2023 workshop chairs for their kind assistance during the organization process. Finally, our thanks go to our gold sponsor iguanodon.ai, as well as the research project "Towards Computational Lexical Semantic Change Detection" (Swedish Research Council, contract 2018-01184) and the research program "Change is Key!" (Riksbankens Jubileumsfond, contract M21-0021).

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Section: Word Embeddings and Discourse Studiesmentioning

confidence: 99%

Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change

2023

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

Gribomont

2023

Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change

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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" (Kranert, 2020). SDKs are therefore a useful contribution to (computational) discourse studies and text-based Digital Humanities more broadly.

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Topic Models and Word Embeddings for Ideological Analysis: A Case Study in Neoliberal Discourse

Cited by 2 publications

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Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change

Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change

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

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