The paper aims to answer the two following questions: 1-“Can we automatically and accurately classify a news article as containing disinformation?” 2- “What characteristics of disinformation differentiate it from other types of benign information?” The paper concludes that fact checking is needed for credibility checks and that style based classifiers are not enough. It also finds that natural language inference automating that is used to automate/ semi-automate fact checking processes, such as web app and FactFinder, are a development in the right direction.
Title
Disinformation: Analysis and Identification
Summary
َAuthor
Pathak, Archita; Srihari, Rohini K; Natu, Nihit
Year
2021
َThematic Area
Computer Studies
Topic
Disinformation
Country
USA
Region
North America
Misinformation Combatting
Detection of Misinformation
Place Published
New York
Publisher
Springer US
Journal
Computational and Mathematical Organization Theory
DOI
https://doi.org/10.1007/s10588-021-09336-x
URL
https://link.springer.com/content/pdf/10.1007/s10588-021-09336-x.pdf
https://link.springer.com/content/pdf/10.1007/s10588-021-09336-x.pdf
APA 7th End Text Citation
Pathak, A., Srihari, R. K., & Natu, N. (2021). Disinformation: analysis and identification. Computational and Mathematical Organization Theory, 27(3), 357–375. https://doi.org/10.1007/s10588-021-09336-x