A Survey on Computational Politics

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Haq , E U , Braud , T , Kwon , Y D & Hui , P 2020 , ' A Survey on Computational Politics ' , IEEE Access , vol. 8 , pp. 197379-197406 . https://doi.org/10.1109/ACCESS.2020.3034983

Title: A Survey on Computational Politics
Author: Haq, Ehsan ul; Braud, Tristan; Kwon, Young D.; Hui, Pan
Contributor: University of Helsinki, Department of Computer Science
Date: 2020-11
Language: eng
Number of pages: 28
Belongs to series: IEEE Access
ISSN: 2169-3536
URI: http://hdl.handle.net/10138/322304
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 political practices such as debates. These communities and digitized data contain both explicit and latent information about users and their behaviors related to politics and social movements. 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.
Subject: cs.SI
cs.CY
Computational politics
SENTIMENT
NETWORKS
VOTERS
REVEAL
social computing
user modelling
computers and information processing
IMPACT
PREDICT
discourse analysis
social network analysis
digital humanities
ELECTION
POLARIZATION
TWITTER
113 Computer and information sciences
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