Social bots weaken activist cohesion

• URL: http://arxiv.org/abs/2609.00197v1
• Date: Mon, 31 Aug 2026 18:13:31 GMT
• Title: Social bots weaken activist cohesion
• Abstract summary: Social bots now make up a substantial share of online political communication.<n>We ask whether exposure to bots during a protest peak is followed by the erosion of cohesion in human networks.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Social bots now make up a substantial share of online political communication, where they are studied mainly as producers of misinformation and amplified content. Far less is known about whether their presence reshapes the human relationships that hold movements together. We ask whether exposure to bots during a protest peak is followed by the erosion of cohesion in human networks. Tracking retweet networks of core participants in the 2020 Black Lives Matter (BLM) protests before, during, and after the peak, we measure change in cohesion at two scales: triadic closure in individual ego networks and edge density within detected communities. Greater bot exposure during the peak predicts steeper subsequent declines in human cohesion at both scales, and the loss concentrates among supporters of the movement. Bots may weaken activism less by changing what people believe than by dissolving the ties through which collective action is sustained.

Related papers

• Synthetic Contact with AI Reduces Cross-Partisan Animosity [0.0]
  Americans' warmth toward members of the opposing political party has fallen sharply over the past three decades.<n>We test whether brief conversations with AI chatbots representing the political outgroup can substitute for the contact people shun.
  arXiv  Detail & Related papers  (2026-07-02T13:51:57Z)
• Reddit Deplatforming and Toxicity Dynamics on Generalist Voat Communities [73.88859384645264]
  Deplatforming, the permanent banning of entire communities, is a primary tool for content moderation on mainstream platforms.<n>We analyze four major Reddit ban waves (2015--2020) and their effects on generalist communities on Voat.
  arXiv  Detail & Related papers  (2025-12-26T19:13:45Z)
• Echoes of Automation: How Bots Shaped Political Discourse in Brazil [0.0]
  Drawing on more than 315 million tweets posted from August 2018 to June 2022, we examine behavioural patterns, sentiment dynamics, and the thematic focus of bot- versus human-generated content.<n>Our analysis shows that bots relied disproportionately on retweets and replies, with reply activity spiking after the 2018 election.<n> Sentiment analysis indicates that bots maintained a narrower emotional tone, in contrast to humans, whose sentiment fluctuated more strongly with political events.
  arXiv  Detail & Related papers  (2025-12-11T15:40:10Z)
• RoBCtrl: Attacking GNN-Based Social Bot Detectors via Reinforced Manipulation of Bots Control Interaction [51.46634975923564]
  This paper proposes the first adversarial multi-agent Reinforcement learning framework for social Bot control attacks (RoBCtrl)<n> Specifically, we use a diffusion model to generate high-fidelity bot accounts by reconstructing existing account data with minor modifications.<n>We then employ a Multi-Agent Reinforcement Learning (MARL) method to simulate bots adversarial behavior.
  arXiv  Detail & Related papers  (2025-10-16T02:41:49Z)
• Sleeper Social Bots: a new generation of AI disinformation bots are already a political threat [0.0]
  "Sleeper social bots" are AI-driven social bots created to spread disinformation and manipulate public opinion. Preliminary findings suggest these bots can convincingly pass as human users, actively participate in conversations, and effectively disseminate disinformation. The implications of our research point to the significant challenges posed by social bots in the upcoming 2024 U.S. presidential election and beyond.
  arXiv  Detail & Related papers  (2024-08-07T19:57:10Z)
• Social bots sour activist sentiment without eroding engagement [0.0]
  We find that bots exert a greater influence on human behavior than vice versa during heated online periods. Political astroturfing bots increase activity, whereas other bots decrease it. Despite the seemingly minor impact of individual bot encounters, the cumulative effect is profound due to the large volume of bot communication.
  arXiv  Detail & Related papers  (2024-03-19T16:58:45Z)
• You are a Bot! -- Studying the Development of Bot Accusations on Twitter [1.7626250599622473]
  In the absence of ground truth data, researchers may want to tap into the wisdom of the crowd. Our research presents the first large-scale study of bot accusations on Twitter. It shows how the term bot became an instrument of dehumanization in social media conversations.
  arXiv  Detail & Related papers  (2023-02-01T16:09:11Z)
• Promoting and countering misinformation during Australia's 2019-2020 bushfires: A case study of polarisation [0.11470070927586014]
  misinformation blaming arson resurfaced on Twitter during Australia's unprecedented bushfires. We study Twitter communities spreading this misinformation during the population-level event, and investigate the role of online communities and bots. We find that Supporters promoted misinformation by engaging others directly with replies and mentions using hashtags and links to external sources. We speculate that the communication strategies observed here could be discoverable in other misinformation-related discussions and could inform counter-strategies.
  arXiv  Detail & Related papers  (2022-01-10T03:44:31Z)
• Identification of Twitter Bots based on an Explainable ML Framework: the US 2020 Elections Case Study [72.61531092316092]
  This paper focuses on the design of a novel system for identifying Twitter bots based on labeled Twitter data. Supervised machine learning (ML) framework is adopted using an Extreme Gradient Boosting (XGBoost) algorithm. Our study also deploys Shapley Additive Explanations (SHAP) for explaining the ML model predictions.
  arXiv  Detail & Related papers  (2021-12-08T14:12:24Z)
• News consumption and social media regulations policy [70.31753171707005]
  We analyze two social media that enforced opposite moderation methods, Twitter and Gab, to assess the interplay between news consumption and content regulation. Our results show that the presence of moderation pursued by Twitter produces a significant reduction of questionable content. The lack of clear regulation on Gab results in the tendency of the user to engage with both types of content, showing a slight preference for the questionable ones which may account for a dissing/endorsement behavior.
  arXiv  Detail & Related papers  (2021-06-07T19:26:32Z)
• On spatial variation in the detectability and density of social media user protest supporters [52.77024349608834]
  The research reported here uses spatial capture-recapture methods to determine the influence of the built environment, physical proximity to protest location, and collective posting rhythm on variations in users' spatial detectability and density during a protest in Mexico City.
  arXiv  Detail & Related papers  (2021-03-10T14:08:08Z)
• Echo Chambers on Social Media: A comparative analysis [64.2256216637683]
  We introduce an operational definition of echo chambers and perform a massive comparative analysis on 1B pieces of contents produced by 1M users on four social media platforms. We infer the leaning of users about controversial topics and reconstruct their interaction networks by analyzing different features. We find support for the hypothesis that platforms implementing news feed algorithms like Facebook may elicit the emergence of echo-chambers.
  arXiv  Detail & Related papers  (2020-04-20T20:00:27Z)
• Quantifying the Vulnerabilities of the Online Public Square to Adversarial Manipulation Tactics [43.98568073610101]
  We use a social media model to quantify the impacts of several adversarial manipulation tactics on the quality of content. We find that the presence of influential accounts, a hallmark of social media, exacerbates the vulnerabilities of online communities to manipulation. These insights suggest countermeasures that platforms could employ to increase the resilience of social media users to manipulation.
  arXiv  Detail & Related papers  (2019-07-13T21:12:08Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.