Misinformation Detection: A Survey of AI Techniques and Research Opportunities
This survey highlights the evolution of techniques within misinformation detection. Misinformation has become increasingly prevalent on the Internet by the day and progressively more threatening. Individuals who are inaccurately informed tend to make misinformed decisions which have led to voting scandals, traffic accidents, and even health concerns. We are motivated to address a research gap by analyzing misinformation detection’s overall progress and exposing the weaknesses that provide research opportunities. Our findings will further advance the work of misinformation detection and bring light to unique ways to tackle the issue. Notably, we discuss the significance of misinformation detection systems and present the problems resulting from misinformation, the techniques for detection, and open issues within this research. Misinformation is becoming an issue that requires more attention and improved systems. We believe that our systematic review and synthesis of state-of-art research will cultivate a path for these developments.
Authors
- Wenting Jiang (ORCID: https://orcid.org/0000-0003-3973-2025)
- Ashish Gupta (ORCID: https://orcid.org/0000-0003-4491-9337)
- Xiao Qin (ORCID: https://orcid.org/0000-0002-8345-3587)
- Gabrielle Taylor (ORCID: https://orcid.org/0000-0001-7960-8745)
Institutions
- Oklahoma State University Oklahoma City (US)
- Universidad Nacional del Altiplano (PE)
- Auburn University (US)
Publication Details
- Journal
- Foundations and Trends® in Information Systems
- Published
- 2024-10-02
- DOI
- https://doi.org/10.1561/2900000037
- Citations
- 1
- Primary Topic
- Misinformation and Its Impacts
- Type
- article
- Field-Weighted Citation Impact
- 1.13