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: - Strategic Opinion Manipulation in Multiplex Networks — formal game-theoretic model of strategic opinion manipulation on multiple platforms; shows how manipulators exploit network structure and platform design (layer merging, attention weights) to move consensus, with implications for platform robustness to coordinated propaganda - A Multi-Stage Agentic Framework for Effective Counter-Narrative Generation and Refinement — multi-stage agent-based framework for generating and refining counter-narratives to computational propaganda; demonstrates scalable LLM-driven approach to narrative defense with human validation and simulated effectiveness testing. - Gerard, Mendelsohn, & Lerman (2026) — unifies six mechanisms of hostile rhetoric used in political discourse (boundary construction, threat construction, scapegoating, negative evaluation, dehumanization, action orientation); demonstrates their structural relationships and temporal organization in 2.86M posts from TikTok, Twitter/X, and Truth Social during 2024 U.S. election - Social bots weaken activist cohesion — Shows how computational propaganda through social bots disrupts not only information flow but also the relational infrastructure needed for collective action; analyzes impact on activist networks during Black Lives Matter protests - 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 - Sánchez-Cortés, Monti & De Francisci Morales (2026) — Conspiracy and Environment Communities on Reddit Sort Along Different Demographic Axes: demonstrates how propaganda and political content reach different audiences through demographically-segregated information pathways; masculine users arrive at conspiracy communities via right-wing media infrastructure, feminine users via esoteric spiritual content; reveals structural mechanisms of demographic targeting in online political ecosystems - Birds of a Feather Flock Together: Network-Based Detection of Coordinated Disinformation Campaigns on Telegram — analyzes computational propaganda on Telegram through graph-based network analysis; characterizes message duplication strategies used to amplify propaganda across echo chambers; identifies cross-platform amplification via YouTube and fake-news sites