Negative Partisanship Networks on Social Media

We develop a network-analytic approach to studying negative partisanship on social media. Rather than measuring affective polarization through survey data, the study conceptualizes negative partisanship as a relational phenomenon observable in patterns of negative political communication on social media. Using Twitter data from the multiparty system of Finland (2015–2023), the paper examines tweets by parliamentary candidates expressing negative sentiments towards other political parties. Party mentions in negative tweets are used to construct two-mode networks linking political actors to the parties they criticize, which are then projected into one-mode networks capturing shared patterns of negative representation. This framework identifies clusters of actors and parties that align through common targets of negativity. The paper shows how negative partisanship networks vary across government and opposition periods and across ideological blocs. By treating negative affect as a networked structure rather than an individual attitude, the study offers a novel way to analyze affective polarization in multiparty systems and demonstrates how social media data can be used to map the relational foundations of partisan hostility.