A Survey on Computational Politics

TL;DR

This survey reviews computational methods used to analyze and influence political behaviors online, categorizing key research areas across various digital platforms and discussing future challenges and opportunities.

Contribution

It provides a comprehensive categorization of computational politics research and summarizes prominent studies across multiple online platforms.

Findings

Identifies main areas in computational politics research.

Summarizes key studies in social networks, forums, and debates.

Highlights future research directions and challenges.

Abstract

Computational Politics is the study of computational methods to analyze and moderate users' behaviors related to political activities such as election campaign persuasion, political affiliation, and opinion mining. With the rapid development and ease of access to the Internet, Information Communication Technologies (ICT) have given rise to massive numbers of users joining online communities and the digitization of analogous data such as political debates. These communities and digitized data contain both explicit and latent information about users and their behaviors related to politics. For researchers, it is essential to utilize data from these sources to develop and design systems that not only provide solutions to computational politics but also help other businesses, such as marketers to increase users, participation and interactions. In this survey, we attempt to categorize main areas in computational politics and summarize the prominent studies in one place to better understand computational politics across different and multidimensional platforms. e.g., online social networks, online forums, and political debates. We then conclude this study by highlighting future research directions, opportunities, and challenges.