mlsanityData to 7 Oct 2026

Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Language

arXiv 2109.07909 ↗First posted 13 Sep 2021cs.CY cs.CL cs.SIcited by 6

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Abstract (arXiv)

With the explosive growth of online social media, the ancient problem of information disorders interfering with news diffusion has surfaced with a renewed intensity threatening our democracies, public health, and news outlets' credibility. Therefore, thousands of scientific papers have been published in a relatively short period, making researchers of different disciplines struggle with an information overload problem. The aim of this survey is threefold: (1) we present the results of a network-based analysis of the existing multidisciplinary literature to support the search for relevant trends and central publications; (2) we describe the main results and necessary background to attack the problem under a computational perspective; (3) we review selected contributions using network science as a unifying framework and computational linguistics as the tool to make sense of the shared content. Despite scholars working on computational linguistics and networks traditionally belong to different scientific communities, we expect that those interested in the area of fake news should be aware of crucial aspects of both disciplines.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 59 of its 296 references that are in the map. First posted on arXiv 13 Sep 2021.

Builds on

59 of 296 references.

References · 59

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38 more
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50 most cited of 59 All 59 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 3; 2025: 1; 2026: 1.

6 papers.

  1. 2023Legend at ArAIEval Shared Task: Persuasion Technique Detection using a Language-Agnostic Text Representation Modelcited by 4
  2. 2024Camouflage is all you need: Evaluating and Enhancing Language Model Robustness Against Camouflage Adversarial Attackscited by 1
  3. 2024A (More) Realistic Evaluation Setup for Generalisation of Community Models on Malicious Content Detectioncited by 1
  4. 2025Emotion-aware Dual Cross-Attentive Neural Network with Label Fusion for Stance Detection in Misinformative Social Media Contentcited by 1
  5. 2024Evaluating the Propensity of Generative AI for Producing Harmful Disinformation During the 2024 US Election Cyclecited by 0
  6. 2026Integration of Deep Reinforcement Learning and Agent-based Simulation to Explore Strategies Counteracting Information Disordercited by 0