mlsanityData to 7 Oct 2026

Methods of Informational Trends Analytics and Fake News Detection on Twitter

arXiv 2204.04891 ↗First posted 11 Apr 2022cs.CL cs.AI cs.SIcited by 6

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Abstract (arXiv)

In the paper, different approaches for the analysis of news trends on Twitter has been considered. For the analysis and case study, informational trends on Twitter caused by Russian invasion of Ukraine in 2022 year have been studied. A deep learning approach for fake news detection has been analyzed. The use of the theory of frequent itemsets and association rules, graph theory for news trends analytics have been considered.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 6 of its 37 references that are in the map. First posted on arXiv 11 Apr 2022.

Builds on

6 of 37 references.

References · 6

  1. 2020Automatic Detection of Machine Generated Text: A Critical Surveycited by 160
  2. 2020TweepFake: about Detecting Deepfake Tweetscited by 117
  3. 2018Fake News Identification on Twitter with Hybrid CNN and RNN Modelscited by 17
  4. 2021Dataset of Fake News Detection and Fact Verification: A Surveycited by 11
  5. 2022Forming Predictive Features of Tweets for Decision-Making Supportcited by 5
  6. 2013Can Twitter Predict Royal Baby's Name ?cited by 4

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Cited by year

Citing papers per year: 2022: 1; 2023: 2; 2024: 1; 2025: 2.

6 papers.

  1. 2023Analysis of Disinformation and Fake News Detection Using Fine-Tuned Large Language Modelcited by 10
  2. 2023Financial News Analytics Using Fine-Tuned Llama 2 GPT Modelcited by 6
  3. 2022Analytics of Business Time Series Using Machine Learning and Bayesian Inferencecited by 1
  4. 2025AI Approaches to Qualitative and Quantitative News Analytics on NATO Unitycited by 1
  5. 2025Multilevel Analysis of Cryptocurrency News using RAG Approach with Fine-Tuned Mistral Large Language Modelcited by 1
  6. 2024Using GPT Models for Qualitative and Quantitative News Analytics in the 2024 US Presidental Election Processcited by 0