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5-6 Sep 2024 Nice (France)
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Keynote speakersSusan C. Herring, Indiana University https://homes.luddy.indiana.edu/herring/
Susan C. Herring is a professor of Information Science in Indiana University, USA, an Adjunct Professor of Linguistics and director of the Center for Computer-Mediated Communication. Her main research areas are technologically-mediated communication, multimodal discourse, and gender and digital technology. She has contributed significantly to the understanding of how language is used in online environments such as social media, forums, and chatrooms. Herring has published numerous academic papers and co-authored books on these topics, making her a prominent figure in the field of internet linguistics.
Large-Scale Analyses of Small-Scale Research Questions: Pros and Cons of Upscaling Computer-Mediated Discourse Analysis
Susan C. Herring
Indiana University, Bloomington USA
Advances in machine learning and generative AI mean that larger CMC corpora can be collected, normalized, analyzed, and managed more efficiently and accurately than ever before. However, in computer-mediated discourse analysis (CMDA), it is generally accepted that certain research questions are best suited for small datasets and manual analysis, due to the need for detailed, nuanced understanding and interpretation of discourse in context (Herring, 2004). Yet automated analyses of large datasets are increasingly addressing traditional CMDA topics such as identity construction, turn-taking, misunderstandings, speech acts, (im)politeness, power dynamics, and humor, and the methods for doing so are getting more sophisticated. In this talk, I will consider what CMDA gains through the latter approach, as well as what is lost if the work required to do CMDA becomes fully automated. I will argue for a mixed methodological approach, while acknowledging that AI-driven change to CMDA is probably inevitable. I will conclude by proposing that the trade-offs involved can be understood by analogy to the invention of writing, the printing press, and the internet, each of which resulted in the loss of older communication practices but represented a significant leap in how humans create, share, and interact with information.
Reference
Herring, S. C. (2004). Computer-mediated discourse analysis: An approach to researching online behavior. In S. A. Barab, R. Kling, & J. H. Gray (Eds.), Designing for virtual communities in the service of elarning (pp. 338-376). New York: Cambridge University Press.
Marco Cappellini, Université Lyon1 - ICAR Laboratory
Corpora in telecollaboration and virtual exchange Marco Cappellini Telecollaboration is a pedagogical practice in which groups of learners in different geographical locations are connected to pursue various objectives. These objectives often include intercultural competence, soft skills such as collaboration, and linguistic skills. Since its inception, telecollaboration has been the focus of empirical studies, particularly on the online interactions among learners. In this talk, I propose to explore corpora in telecollaboration from two perspectives. After an introduction that delimits the field of inquiry to telecollaboration, the first part will explore how researchers have collected and analyzed data throughout the history of telecollaboration. I will emphasize how researchers adapted to technological changes, moving from written asynchronous exchanges to current exchanges distributed across platforms. These platforms include asynchronous written communication, online social media, and synchronous audio-visual communication. I will also show how qualitative studies predominate in the field and point out relevant exceptions. The second part of my talk will summarize the studies in telecollaboration that specifically deal with corpus building and analysis, especially (semi)automatic analysis. The presentation will conclude with an opening and a proposal to study multimodality in corpora of videoconference-based telecollaboration, based on my experience with the Vapvisio project... References Cappellini, M., Holt, B., Bigi, B., Tellier, M., & Zielinski, C. (2023). A multimodal corpus to study videoconference interactions for techno-pedagogical competence in second language acquisition and teacher education. Corpus, 24. https://doi.org/10.4000/corpus.7440 Guichon, N. (2017). Sharing a multimodal corpus to study webcam-mediated language teaching. Language Learning & Technology, 21(1), 55-74. Helm, F., & Dooly, M. (2017). Challenges in transcribing multimodal data: A case study. Language Learning & Technology, 21(1), 166-185.
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