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<p>The most successful uses of generative AI in social science up to this point have been limited several ways, mostly processing text-only data for simple and sharply delineated tasks, such as thematic analysis and hate speech detection, and frequently requiring training or fine-tuning of the AI model before use. The present study greatly expands the space of possible applications of generative AI in social science by demonstrating the ability of Gemini 2.5 Pro, a current frontier Large Language Model (LLM), to conduct comprehensive discourse analyses of multimodal (text, image, and video) social media posts, taking into consideration the broader social, political, cultural, and technological context of those posts. Using AI to conduct this sort of analysis requires the researcher to create detailed instructions to guide the analysis, but not any additional training or fine-tuning—the model’s zero-shot (“off-the shelf”) performance is more than adequate. The analysis of each post also takes a few minutes at most, even when processing videos up to 60 min long, enabling in-depth, open-ended analyses of large corpora that were not previously feasible, which in turn enables academic researchers, content moderators, and law enforcement, among others, to study and review orders of magnitude more data than they previously could.</p>

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Instant understanding: LLM zero-shot qualitative discourse analysis of multimodal social media content

  • 期刊论文

  • 发表日期：

    2026年6月18日

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  • Dustin Tucker,
  • Giovanna L. Henery

摘要

The most successful uses of generative AI in social science up to this point have been limited several ways, mostly processing text-only data for simple and sharply delineated tasks, such as thematic analysis and hate speech detection, and frequently requiring training or fine-tuning of the AI model before use. The present study greatly expands the space of possible applications of generative AI in social science by demonstrating the ability of Gemini 2.5 Pro, a current frontier Large Language Model (LLM), to conduct comprehensive discourse analyses of multimodal (text, image, and video) social media posts, taking into consideration the broader social, political, cultural, and technological context of those posts. Using AI to conduct this sort of analysis requires the researcher to create detailed instructions to guide the analysis, but not any additional training or fine-tuning—the model’s zero-shot (“off-the shelf”) performance is more than adequate. The analysis of each post also takes a few minutes at most, even when processing videos up to 60 min long, enabling in-depth, open-ended analyses of large corpora that were not previously feasible, which in turn enables academic researchers, content moderators, and law enforcement, among others, to study and review orders of magnitude more data than they previously could.