Presentation for NECS Conference: "Addressing Key Research Questions in Film and Audience Studies With Artificial Intelligence Tools Conceived for Focus Groups"

This presentation examines how computer science and film studies can be combined in an interdisciplinary crossover greater than the sum of its parts. Methodologies such as focus groups can provide the film and media studies field insight into audience perception, reception, and engagement. However, logistical and conceptual complexities often restrict the use of focus groups. In response to these limitations, AI-powered tools are emerging as innovative alternatives, offering new ways to analyse audience responses with greater efficiency and depth. This presentation intends to demonstrate how artificial intelligence can be organically integrated into focus group methodologies to answer key research questions in film studies, especially those concerning audiences, their preferences and their reactions to different types of film.

Drawing on research conducted within the CresCine project (Horizon Europe), this study investigates the potential of AI-driven tools to assess audience reactions to films from small European countries. Through natural language processing and sentiment analysis, AI can identify recurring themes, implicit biases, and emotional responses within focus group discussions, allowing for a more systematic exploration of how viewers engage with film and media. This approach not only refines audience research but also enhances the analytical capabilities of film studies by providing empirical support for interpretive analysis.

The paper starts by examining the relevance of focus groups and audience research within the context of CresCine to establish a contextual background. Then, it explains how we are navigating those task with the help of the in-house developed tool, CineLytics. By revealing its inner works and preliminary results of its application, we intend to demonstrate its potential and reach to examine audiences and tackle issues related to film studies. We will show how this AI model can uncover patterns in the discourse of focus group participants and offer a more nuanced understanding of cultural perceptions, symbolic relevance and taste than what the current literature offers. This research intends to contribute in equal measure to broader discussions on the competitiveness of the film industries from small European countries and on innovative ways to address old issues in the fields of film and audience studies.