Deception detection for news: Three types of fakes
Indexed incrossref
Abstract
ABSTRACT A fake news detection system aims to assist users in detecting and filtering out varieties of potentially deceptive news. The prediction of the chances that a particular news item is intentionally deceptive is based on the analysis of previously seen truthful and deceptive news. A scarcity of deceptive news, available as corpora for predictive modeling, is a major stumbling block in this field of natural language processing (NLP) and deception detection. This paper discusses three types of fake news, each in contrast to genuine serious reporting, and weighs their pros and cons as a corpus for text analytics and predictive modeling. Filtering, vetting, and verifying online information continues to be…
Citation impact
541
total citations
- FWCI
- 61.82
- Percentile
- 100%
- References
- 18
Citations per year
Authors
3Topics & keywords
Topics
Keywords
- Vetting
- Deception
- Fake news
- Computer science
- Internet privacy
- Disinformation
- Data science
- Social media
No related works found for this paper.