Computational politics

Computational Politics is the intersection between computer science and political science. The area involves the usage of computational method such as analysis tools, prediction methods to present the solutions to political sciences questions. Researchers in this area use large sets of data to study user behavior.[1] Common examples of such works are building a classifier to predict users' political bias in social media or finding political bias in the news. This discipline is closely related with Digital Sociology. However, the main focus is on political related problems and analysis.

Computational politics is often discussed together with policy and public opinion engineering. Ashu M. G. Solo highlights the need of technocracy in democratic process where decision makers can make decision, e.g. where and how to spend the campaign money[2] Although the political canvas is wide, Haq et al. categorise the work in to five main major categories [3]

  1. Community and User Modelling
  2. Information Flow
  3. Political Discourse
  4. Election Campaigns
  5. System Design.

References
  1. Winston, Patrick H.; Finlayson, Mark A. "Computational Politics". S2CID 7589841. Cite journal requires |journal= (help)
  2. Solo, Ashu MG. "The new fields of public policy engineering, political engineering, computational public policy, and computational politics." Proceedings of the International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government (EEE). The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp), 2011.
  3. Haq, Ehsan U.; Braud, Tristan; Kwon, Young D.; Hui, Pan (2019). "A Survey On Computational Politics". arXiv:1908.06069 [cs.SI].


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