Computational Propaganda¶
Computational propaganda refers to the use of algorithms, automation, data, and computational techniques to manipulate public opinion, amplify propaganda, and conduct coordinated inauthentic behavior at scale. It encompasses bot networks, troll farms, algorithmic amplification, and state-sponsored disinformation campaigns that leverage computing and data science to achieve political objectives.
Key talks and papers¶
Talks: - Barabási — Information and Misinformation Spread on Social Networks — network science perspective on social bots as tools for computational amplification; discusses bot manipulation strategies (making politicians appear popular, stock market manipulation, disrupting protests) and the scale of inauthentic accounts on major platforms - Social Bots and Misinformation: Detection, Diffusion, and Mitigation — analysis of how bots are deployed in coordinated campaigns for political manipulation, vaccine misinformation, and election interference; empirical evidence from diffusion networks showing bot strategies (early amplification, targeting influencers) and their effectiveness at making content appear artificially popular
Papers: - A Survey on Computational Propaganda Detection — comprehensive survey of computational propaganda detection approaches; distinguishes propaganda (persuasion) from disinformation (falsity); defines computational propaganda as created/disseminated via automated means; covers both text analysis (NLP) and network analysis (bot/coordination detection) perspectives; identifies key challenge of disconnection between NLP and network analysis communities - Characterizing the Use of Images in State-Sponsored Information Warfare Operations — empirical characterization of Russian state-sponsored propaganda operations; demonstrates strategic use of images and memes for computational amplification across platforms