Social networks are huge continuous sources of information that can be used to analyze people's behavior and thoughts. Our goal is to extract such information and predict political inclinations of users. In particular, we investigate the importance of syntactic features of texts written by users when they post on social media. Our hypothesis is that … Continue reading Content-based Classification of Political Inclinations of Twitter Users
We implemented an RNN-based analysis that aim to gauge local support for the two major US political parties in the 68 most competitive House of Representative districts during the 2018 U.S. mid-term elections.
Predicting the outcome of elections is a topic that has been extensively studied in political polls, which have generally provided reliable predictions by means of statistical models. In recent years, online social media platforms have become a potential alternative to traditional polls, since they provide large amounts of post and user data, also referring to … Continue reading Understanding Polarized Political Events through Social Media Analysis
