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Mining Disinformation and Fake News: Concepts, Methods, and Recent Advancements

arXiv 2001.00623 ↗First posted 2 Jan 2020cs.SI cs.CLcited by 17

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Abstract (arXiv)

In recent years, disinformation including fake news, has became a global phenomenon due to its explosive growth, particularly on social media. The wide spread of disinformation and fake news can cause detrimental societal effects. Despite the recent progress in detecting disinformation and fake news, it is still non-trivial due to its complexity, diversity, multi-modality, and costs of fact-checking or annotation. The goal of this chapter is to pave the way for appreciating the challenges and advancements via: (1) introducing the types of information disorder on social media and examine their differences and connections; (2) describing important and emerging tasks to combat disinformation for characterization, detection and attribution; and (3) discussing a weak supervision approach to detect disinformation with limited labeled data. We then provide an overview of the chapters in this book that represent the recent advancements in three related parts: (1) user engagements in the dissemination of information disorder; (2) techniques on detecting and mitigating disinformation; and (3) trending issues such as ethics, blockchain, clickbaits, etc. We hope this book to be a convenient entry point for researchers, practitioners, and students to understand the problems and challenges, learn state-of-the-art solutions for their specific needs, and quickly identify new research problems in their domains.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Jan 2020.

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Citing papers per year: 2021: 5; 2022: 3; 2023: 3; 2024: 4; 2025: 2.

17 papers.

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  1. 2021Deepfakes Generation and Detection: State-of-the-art, open challenges, countermeasures, and way forwardcited by 82
  2. 2022Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methodscited by 75
  3. 2024Can Large Language Models Identify Authorship?cited by 40
  4. 2022Targeted Phishing Campaigns using Large Scale Language Modelscited by 22
  5. 2021Knowledge Graph informed Fake News Classification via Heterogeneous Representation Ensemblescited by 14
  6. 2023An Empirical Study of AI Generated Text Detection Toolscited by 9
  7. 2023Chatbots to ChatGPT in a Cybersecurity Space: Evolution, Vulnerabilities, Attacks, Challenges, and Future Recommendationscited by 7
  8. 2021Mitigation of Diachronic Bias in Fake News Detection Datasetcited by 5
  9. 2023ExClaim: Explainable Neural Claim Verification Using Rationalizationcited by 4
  10. 2024Quantitative Analysis of AI-Generated Texts in Academic Research: A Study of AI Presence in Arxiv Submissions using AI Detection Toolcited by 3
  11. 2021Deriving Disinformation Insights from Geolocalized Twitter Calloutscited by 0
  12. 2021Human-in-the-Loop Disinformation Detection: Stance, Sentiment, or Something Else?cited by 0
5 more
  1. 2022Graphical Models of False Information and Fact Checking Ecosystemscited by 0
  2. 2024FNDEX: Fake News and Doxxing Detection with Explainable AIcited by 0
  3. 2024Do Voters Get the Information They Want? Understanding Authentic Voter FAQs in the US and How to Improve for Informed Electoral Participationcited by 0
  4. 2025Enhancing Social Media Rumor Detection: A Semantic and Graph Neural Network Approach for the 2024 Global Electioncited by 0
  5. 2025Leveraging Knowledge Graphs and LLMs for Structured Generation of Misinformationcited by 0