mlsanityData to 14 Oct 2026

Investigating Online Financial Misinformation and Its Consequences: A Computational Perspective

arXiv 2309.12363 ↗First posted 6 Sep 2023cs.CY cs.AIcited by 8

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Abstract (arXiv)

The rapid dissemination of information through digital platforms has revolutionized the way we access and consume news and information, particularly in the realm of finance. However, this digital age has also given rise to an alarming proliferation of financial misinformation, which can have detrimental effects on individuals, markets, and the overall economy. This research paper aims to provide a comprehensive survey of online financial misinformation, including its types, sources, and impacts. We first discuss the characteristics and manifestations of financial misinformation, encompassing false claims and misleading content. We explore various case studies that illustrate the detrimental consequences of financial misinformation on the economy. Finally, we highlight the potential impact and implications of detecting financial misinformation. Early detection and mitigation strategies can help protect investors, enhance market transparency, and preserve financial stability. We emphasize the importance of greater awareness, education, and regulation to address the issue of online financial misinformation and safeguard individuals and businesses from its harmful effects. In conclusion, this research paper sheds light on the pervasive issue of online financial misinformation and its wide-ranging consequences. By understanding the types, sources, and impacts of misinformation, stakeholders can work towards implementing effective detection and prevention measures to foster a more informed and resilient financial ecosystem.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 5 of its 212 references that are in the map. First posted on arXiv 6 Sep 2023.

Builds on

5 of 212 references.

References · 5

  1. 2023BloombergGPT: A Large Language Model for Financecited by 939
  2. 2017Fake News Detection on Social Media: A Data Mining Perspectivecited by 336
  3. 2017The spread of low-credibility content by social botscited by 73
  4. 2022MDFEND: Multi-domain Fake News Detectioncited by 68
  5. 2020BanFakeNews: A Dataset for Detecting Fake News in Banglacited by 40

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 2; 2025: 2; 2026: 3.

8 papers.