Call for Papers

Special Issue in Discourse & Society

https://journals.sagepub.com/home/das

Critical Discourse Studies and GenAI

Majid KhosraviNik, Newcastle University

Hossein Kermani, Vienna University

Since its introduction, GenAI has revolutionised many aspects of the sociopolitical sphere in recent years. Technologies like Large Language Models (LLMs) and, in particular, its baby poster, ChatGPT, have already been the topic of many studies in different fields, from political science to psychology and communication (Bail, 2023; Gilardi et al., 2023). Despite, the obvious relevance of GenAI to working assumptions of Critical Discourse Studies (CDS), our knowledge of the nature, quality, and multifaceted implications of this computational breakthrough in discourse production, distribution, and consumption across various contexts is minimal. AI could be viewed as the new phase in forcing reconsideration, and re-examination of the dynamic of discourse in society, following on and going beyond the postulated phase of Social Media Communication (SMC) paradigm (KhosraviNik 2017, 2022, 2023). Both the input and output of many GenAI technologies are largely textual (in broad sense of linguistic, multimodal and multimedia) and, as a result, yield discursive dimensions. For instance, the questions of which power structures these creative meaning making tools enforce or mitigate are relatively understudied (Luitse & Denkena, 2021). At a broad level, we could scrutinise which discourses are substantiated by e.g. LLMs and how these models interact with the existing discourses-in-place. There are also questions about the working definitions of discourse materiality as ‘naturally occurring language’ and its relation to the notion of discursive power.

CDS now carries established credentials in tackling social ills and inequalities through the prism of discourse conceptualisation. This includes socio-politics of group identity and Self-Other constructions. The developments in digital media GenAI are now part of these research foci. Some critical explorations, and problematisation around AI and its social impacts on racism and gender bias are already emerging (see e.g. Adib-Moghaddam 2023, Noble 2018, Siapera 2022). This Special Issue, however, aims to bring in a specifically CDS perspective to the field. It pertains to how a Critical Discourse Studies frame can be envisaged theoretically and methodologically for the new socio-technological dynamic as well as the way AI may interact with resident discourses of racism, gender inequality, ethnic discrimination, and political Self- Othering.

In addition to various levels and types of conceptual considerations, GenAI such as LLMs could bear potential as analytical tools of paramount interest to CDS and its methodological processes -including but also beyond quantification. At its textual level, in one way or another, CDS is tasked with ‘text’ analysis, a job that is now arguably done by LLMs. Prior to LLMs as zero-shot models, other supervised and unsupervised machine algorithms like topic modeling or BERT have been adapted to automatedly analyse large text data (Barberá et al., 2021; Kermani, 2023). While the debate about the potential and weaknesses of such models is ongoing, the arrival of LLMs changes the game entirely. Nonetheless, there is a dearth of knowledge of the capabilities and shortcomings of LLMs in discourse analysis, which could be tackled. Whilst there is growing literature examining LLMs’ power in annotating texts, these studies ordinarily lack the conceptual insights from discourse studies and often end up doing pre-defined annotation tagging hence missing subtle and interpretive dynamics of meaning-making (De Grove et al., 2020; Gilardi et al., 2023). As such, there is a missed body of scholarship in dealing with discursive constructs such as metaphors or argumentation among others. 

As the rapid development of models adds to the emerging complexity at both theory and methodology ends, it remains a fact that CDS cannot continue the business as usual similar to changes to other frames of inquiry in social sciences. To envisage a specific CDS take on this nascent field, there is a need for interdisciplinary deliberation to formulate questions, identify the challenges and elaborate on opportunities while acknowledging the ambitiousness of the task at hand. In addition to emerging few studies on LLMs and  CDS  (e.g. Gillings et al., 2024), there is certainly room to identify perspectives, problematise working notions, and apply methodologies at the intersection of GenAI and CDS. This is, ultimately, about the CDS’ claim to provide critical explanations for the socio-political characteristics of societies and the way power (relations) is established through discourses. We go where discourse goes, and (important degrees of) discourse is now entangled with these technological developments.

Such an endeavor is interdisciplinary by definition and invites empirical studies, theoretical engagements, critical reflections, and methodological considerations from scholars in different fields, such as computer science, discourse studies (in its broad sense), social sciences, political communication, media and technology, digital geography, and Informatics to discuss timely topics including but not limited to:

-   Problematisation of mediation processes and its impact on discourse: how AI can be viewed in connection with past, present and future of CD

-   Theoretical mapping for a viable, principled CDS analysis in the new contexts

-   The way GenAI or in particular LLMs reinforce or undermine power relations and discourses in communication, media, and public opinion.

-   The way GenAI or in particular LLMs may contribute to the evolution or transformation of discourses of Hate Speech, Racism, Gender bias, Islamophobia, etc., across different domains (e.g., media, politics, education).

-   Innovative methodologies for analysing the interplay between GenAI of various content types (language, videos, and other multimodal trends) and discourse within CDS frameworks.

-   The capabilities and shortcomings of LLMs as a viable tool in CDS and their mutual interactions

-   The methodological innovations to conduct multimodal discourse analysis using GenAI technologies

Submission Process:

Authors are invited to submit abstracts (approximately 500 words, all-inclusive) outlining the manuscript's approach, objectives, and relevance. The abstract should demonstrate how the paper contributes to the synergic understanding of the field.

Please submit the abstract and author information to guest editors (Majid.Khosravinik@newcastle.ac.uk and hossein.kermani@univie.ac.at) by June 2, 2025. Please use ‘Submission for the SI on CDS and GenAI’ as the email subject. Abstracts should be formatted as: title, author names, affiliations and contact information, main text, keywords (up to five), along with short bio/s of the author/s. Notifications regarding invitations for full papers will be sent by July 1, 2025. Full papers should be submitted by December 15, 2025.

Refs

Adib-Moghaddam, A. (2023) Is Artificial Intelligence Racist? The Ethics of AI and the Future of Humanity. Bloomsbury.

Noble, N., S. (2018) Algorithms of Oppression: How Search Engines Reinforce Racism. New York University Press

Bail, C. A. (2023). Can Generative AI Improve Social Science? [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/rwtzs

Barberá, P., Boydstun, A. E., Linn, S., McMahon, R., & Nagler, J. (2021). Automated Text Classification of News Articles: A Practical Guide. Political Analysis, 29(1), 19–42. https://doi.org/10.1017/pan.2020.8

De Grove, F., Boghe, K., & De Marez, L. (2020). (What) Can Journalism Studies Learn from Supervised Machine Learning? Journalism Studies, 21(7), 912–927. https://doi.org/10.1080/1461670X.2020.1743737

Gilardi, F., Alizadeh, M., & Kubli, M. (2023, March 27). ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks. arXiv.Org. https://doi.org/10.1073/pnas.2305016120

Gillings, M., Kohn, T., & Mautner, G. (2024). The rise of large language models: Challenges for Critical Discourse Studies. Critical Discourse Studies, 1–17. https://doi.org/10.1080/17405904.2024.2373733

Kermani, H. (2023). Framing the Pandemic on Persian Twitter: Gauging Networked Frames by Topic Modeling. American Behavioral Scientist, 00027642231207078. https://doi.org/10.1177/00027642231207078

KhosraviNik, M. (2017) Social Media Critical Discourse Studies. J. Flowerdew, J. Richardson (Eds.), Handbook of Critical Discourse Analysis, Routledge, London (2017), pp. 582-596

KhosraviNik, M. (2022) Digital meaning-making across content and practice in social media critical discourse studies. Critical Discourse Studies, Vol 19(2): 119-123. Special Issue on SM-CDS.

KhosraviNik, M. (2023) Connecting the digital with the social in digital discourse. In M. KhosraviNik (ed) Social Media and Society: Integrating the digital with the social in digital discourse. John Benjamins. PP 1-15.

Luitse, D., & Denkena, W. (2021). The great Transformer: Examining the role of large language models in the political economy of AI. Big Data & Society, 8(2), 20539517211047734. https://doi.org/10.1177/20539517211047734

Siapera, E. (2022) AI content moderation, racism and (de) coloniality. International journal of Bullying Prevention. 4(1) 55-65.