Gabriele Pinto, Post-Doc Research Fellow at Sapienza University of Rome
Date: 13 FEBRUARY 2025 from 13:00 to 15:00
Event location: Aula 4 - In presence and online event
Type: Guest Seminars Series
Videos have become the preferred and most consumed medium of political communication, surpassing the primacy of textual communication. While the computational analysis of textual data (text-as-data) is well-established in the social sciences, computational methods for video analysis remain relatively underexplored despite their significant potential. We aim to contribute to fill this methodological gap by discussing the use of machine learning tools for computer vision and audio analysis to extract data from videos. To explore the potentials of using these tools, we present a case study where we construct a granular second-by-second dataset of over 2,000 episodes of prominent Italian Political Talk Shows (PTS). We show how to extract information regarding who is speaking, when they are speaking, what they are speaking about, and how they are speaking (tone of the voice and face emotion). To showcase the value of this data, we provide a descriptive analysis of the trends observed in terms of representation, topics discussed, and emotional behaviors, unveiling overt but also subtle forms of slant. We then match the extracted data to minute-by-minute TV viewership data from Auditel™ to describe how different settings are related to changes in viewership, showing that heated discussion, and the presence of non-politicians’ speakers tend to garner higher audience.