Speakers
Description
Social media are a fundamental arena in the context of electoral campaigns, offering a new dynamic space for political communication and public engagement. During elections, these platforms are not only used by political actors to share and disseminate content, but they are also a space where users interact, express their opinions, and influence each other. User comments, in particular, represent a valuable source of information for analyzing patterns of interaction and the circulation of sentiment within the online public sphere.
In this study, we investigate user interaction in two different social media platforms in the two months preceding the 2024 European Election in Italy, covering the period from April 2024 to June 2024. We retrieved the posts and the comments of different political leaders. Based on this data, we extracted the comments and constructed a direct one-mode network among users that captures the structure and the intensity of comment-based exchanges.
To enrich the analysis, we applied sentiment analysis techniques to each comment, allowing us to assign a polarity score to interactions. This enabled the construction of a signed network, where edges represent either positive or negative sentiment between users. We then tested structural balance theories on the network of interactions. This provided a framework for examining not only the topology of online political discussion but also the affective dynamics that characterize user engagement during electoral periods, making it possible to compare the different dynamics present in each profile and identify processes of polarization among user interactions.
Keywords/Topics
Text analysis; Social network analysis; Sentiment analysis; European elections, Signed Network
