LLMSS 2026 – Large Language Models and the Social Sciences Conference: Everything You Need to Know

What Is LLMSS 2026?

The Large Language Models and the Social Sciences Conference (LLMSS 2026) is an inaugural three-day event hosted at City University of Hong Kong, running from October 14 to October 16, 2026. Organized by EPS Academic, this conference marks a dedicated effort to bridge two rapidly converging fields: advanced AI language models and the methodologies of social science research. The event is designed as a cross-disciplinary forum where AI researchers, social scientists, and industry practitioners can examine how large language models are reshaping research methodologies, data analysis, and theoretical frameworks across the social sciences.

LLMSS 2026 arrives at a critical juncture. As LLMs become embedded in everything from survey design to ethnographic coding, social scientists are grappling with both unprecedented analytical power and new epistemological challenges. The conference aims to provide a structured environment for debating these shifts—covering how LLMs can augment qualitative analysis, transform quantitative text mining, and even challenge long-held assumptions about agency and meaning in human communication. By convening at City University of Hong Kong, a hub for both technology and social research in Asia, the event signals a growing recognition that the social sciences must actively shape—not merely react to—the LLM revolution.

Why It Matters for AI Professionals

For AI professionals, LLMSS 2026 offers a rare opportunity to step outside the engineering-centric bubble and engage directly with the domains where LLMs have their most profound societal impact. Social scientists are not just end-users of language models; they are increasingly becoming critics, co-designers, and unexpected innovators of AI systems. Understanding their methodological needs—such as bias auditing, interpretability requirements, and longitudinal data handling—can directly inform better model design and deployment strategies.

Attendees will gain exposure to emerging use cases that often fly under the radar at mainstream AI conferences. From computational sociology to digital ethnography, the social sciences are developing novel evaluation frameworks and prompting strategies that could influence how we benchmark and refine LLMs. For AI professionals working in NLP, responsible AI, or human-computer interaction, LLMSS 2026 provides a focused venue to collaborate with domain experts who can ground technical work in real-world social theory and empirical rigor.

What to Expect

While the full program is still under development, LLMSS 2026 is structured around three core pillars that reflect the conference’s mission:

• Research Methodologies: Sessions exploring how LLMs are being integrated into qualitative coding, survey generation, content analysis, and mixed-methods research. Expect discussions on validity, reproducibility, and the changing role of the human researcher.
• Data Analysis Innovations: Technical tracks focused on using LLMs for large-scale text analysis, sentiment modeling, network analysis, and the extraction of sociologically meaningful patterns from unstructured data.
• Theoretical Frameworks: Panels and keynotes addressing how LLMs challenge existing social theories—from theories of language and meaning to models of social interaction, power, and culture.

Notable speakers and detailed session listings are to be announced. The conference will also feature poster sessions and networking breaks designed to foster cross-disciplinary dialogue between AI engineers and social science faculty.

Who Should Attend

LLMSS 2026 is tailored for a diverse audience. AI researchers and NLP engineers interested in the societal applications of their work will find fertile ground for collaboration. Social science academics—including sociologists, political scientists, anthropologists, and communication scholars—who are actively using or critiquing LLMs in their research will benefit from dedicated methodological tracks. Industry practitioners working in market research, public policy analysis, user experience, or computational social science are also strongly encouraged to attend. Graduate students and early-career researchers looking to establish themselves at this interdisciplinary intersection will find mentorship and networking opportunities.

How to Register

Registration details, including pricing tiers and early-bird deadlines, are to be announced. For the most current information and to secure your place at this inaugural event, visit the official conference website at eps-academic.org/ai-conference. All updates regarding the program, speakers, and registration will be posted there as they become available.