Skip down to main content

Computational Propaganda

Published on
17 Feb 2018

Abstract

Social media can have an impressive impact on civic engagement and political discourse. Yet increasingly we find political actors using digital media and automated scripts for social control. Computational propaganda—through bots, botnets, and algorithms—has become one of the most concerning impacts of technology innovation. Unfortunately, bot identification and impact analysis are among the most difficult research challenges facing the social and computer sciences. COMPROP objectives are to advance a) rigorous social and computer science on bot use, b) critical theory on digital manipulation and political outcomes, c) our understanding of how social media propaganda impacts social movement organization and vitality. This project will innovate through i) “real-time” social and information science actively disseminated to journalists, researchers, policy experts and the interested public, ii) the first detailed data set of political bot activity, iii) a deepened regional expert network able to detect bots and their impact in Europe. COMPROP will achieve this through multi-method and reflexive work packages: 1) international qualitative fieldwork with teams of bot makers and computer scientists working to detect bots; 2a) construction of an original event data set of incidents of political bot use and 2b) treatment of the data set with fuzzy set and traditional statistics; 3) computational theory for detecting political bots and 4) a sustained dissemination strategy. This project will employ state-of-the-art “network ethnography” techniques, use the latest fuzzy set / qualitative comparative statistics, and advance computational theory on bot detection via cutting-edge algorithmic work enhanced by new crowd-sourcing techniques. Political bots are already being deployed over social networks in Europe. COMPROP will put the best methods in social and computer science to work on the size of the problem and the possible solutions.

Details

Professor Philip Howard, University of Oxford
Funder: European Research Council
Award: €1,980,112
Proposal Number: 648311
Dates: 2015-2020
Extended Abstract COMPROP
Full Scientific Description of the Action
Privacy Overview
Oxford Internet Institute

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Strictly Necessary Cookies
  • moove_gdrp_popup -  a cookie that saves your preferences for cookie settings. Without this cookie, the screen offering you cookie options will appear on every page you visit.

This cookie remains on your computer for 365 days, but you can adjust your preferences at any time by clicking on the "Cookie settings" link in the website footer.

Please note that if you visit the Oxford University website, any cookies you accept there will appear on our site here too, this being a subdomain. To control them, you must change your cookie preferences on the main University website.

Google Analytics

This website uses Google Tags and Google Analytics to collect anonymised information such as the number of visitors to the site, and the most popular pages. Keeping these cookies enabled helps the OII improve our website.

Enabling this option will allow cookies from:

  • Google Analytics - tracking visits to the ox.ac.uk and oii.ox.ac.uk domains

These cookies will remain on your website for 365 days, but you can edit your cookie preferences at any time via the "Cookie Settings" button in the website footer.