Political Communities on Twitter: Case Study of the 2022 French Presidential Election
This work addresses the need to understand online political campaigning and supporter demographics for researchers and policymakers, but it is incremental as it applies existing methods to a new election context.
The paper tackled the problem of identifying and analyzing political communities on Twitter during the 2022 French presidential election, resulting in the creation of a dataset with 1.2 million users and 62.6 million tweets, and providing insights into community stances, offensive content, and bot activity.
With the significant increase in users on social media platforms, a new means of political campaigning has appeared. Twitter and Facebook are now notable campaigning tools during elections. Indeed, the candidates and their parties now take to the internet to interact and spread their ideas. In this paper, we aim to identify political communities formed on Twitter during the 2022 French presidential election and analyze each respective community. We create a large-scale Twitter dataset containing 1.2 million users and 62.6 million tweets that mention keywords relevant to the election. We perform community detection on a retweet graph of users and propose an in-depth analysis of the stance of each community. Finally, we attempt to detect offensive tweets and automatic bots, comparing across communities in order to gain insight into each candidate's supporter demographics and online campaign strategy.