2019/06/21 by Alicia Wanless · 1 citation
Social Sciences · #Computer science #Disinformation #Law #Media studies #Misinformation and Its Impacts #Political science #Politics #Reading (process) #Social media #Sociology #The Internet #World Wide Web
paper · doi:10.1093/joc/jqz020
openalex publication_date 2019/06/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
Two books published in November 2018 explore changing tactics of and methods for analysing propaganda in a digital space. Computational Propaganda: Political Parties, Politicians, and Political Manipulation on Social Media edited by Samuel C. Wooley and Philip N. Howard picks up on earlier research by the duo analysing the automated spread of propaganda using social media. Network Propaganda: Manipulation, Disinformation, and Radicalization in American Politics by Yochai Benkler, Robert Faris, and Hal Roberts is available from Oxford University Press in Paperback (472 pages, £18.99) and Hardback (472 pages, £64.00) formats. While both books are valuable reading for the practitioner and academic alike, they highlight the emerging nature of this field, and as such scratch the surface of a complex topic. In the reading of these two books, it becomes clear that much more research is still required into how propaganda is changing in a Digital Age. Computational Propaganda (Wooley & Howard, 2018) is a collection of case studies by various researchers following a similar method developed by the book’s editors through the Oxford Internet Institute’s Project on Computational Propaganda (Wooley & Howard, 2016; Kollanyi, Howard, & Wooley, 2016). This approach to analysing propaganda online has heavily focused on automated Twitter activity and so-called bot networks. Indeed, out of nine case studies, in Computational Propaganda, eight covered Twitter bots as a cornerstone of computational propaganda. Given that Wooley and Howard defined computational propaganda ‘as the use of algorithms, automation, and human curation to purposefully manage and distribute misleading information over social media networks’ (4), the book’s focus on Twitter automation covers only a small subset of what computational propaganda is as a concept. This narrow focus also suggests that this is initial research into an emerging field which needs further investigation into other aspects of it, in particular the use of big data to drive behavioural advertising, or the analysing, segmenting and targeting of audiences using information about individuals to create and deliver persuasive messaging (Wanless & Berk, 2019). Twitter automation, and indeed other social network activity, are components of a wider computational propaganda system, which itself badly needs investigating and the book’s authors should be strongly encouraged to branch out beyond Twitter automation.