Network analysis on political election: populist vs social emergent behaviour

Abstract

Social networks play an important role in people's daily socialization, particularly through social media platforms, which have become key channels for communication and information dissemination. The digital ecosystem does not only evolve communication on multi-network (like TV, social media, and online newspapers) but also provides the social researcher with useful data to explain social-complex dynamics. Our work focuses on cultural dynamics-reactions that occurred during the 2020 Emilia-Romagna elections'' in Italy, where a stronghold culture felt in danger of losing against the strong populism and Euro-scepticism present in digital ecosystems. We would like to show how the interaction between parts of society, during cultural and/or political shifting, can lead to or induce emerging behavior from society, creating groups that react against or improve the status quo. We developed a word-entry network based on three different levels of participation: pro, con, and neutral. We have analyzed the tweets collected (as text) with the word embedding tools, to see, the most used words (which may suggest the main topics) and the most related words among the various groups. We show how a careful analysis of groups through networks, can give important information about the current event.