A Reliable Weighting Scheme for the Aggregation of Crowd Intelligence to Detect Fake News
Social networks play an important role in today’s society and in our relationships with others. They give the Internet user the opportunity to play an active role, e.g., one can relay certain information via a blog, a comment, or even a vote. The Internet user has the possibility to share any conten...
Main Authors: | Franklin Tchakounté, Ahmadou Faissal, Marcellin Atemkeng, Achille Ntyam |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-06-01
|
Series: | Information |
Subjects: | |
Online Access: | https://www.mdpi.com/2078-2489/11/6/319 |
Similar Items
-
CNMF: A Community-Based Fake News Mitigation Framework
by: Shaimaa Galal, et al.
Published: (2021-09-01) -
Influences on the Ability to Recognise Fake News
by: Li, Yunong
Published: (2019) -
Characteristics of Fake News and Misinformation in Greece: The Rise of New Crowdsourcing-Based Journalistic Fact-Checking Models
by: Evangelos Lamprou, et al.
Published: (2021-07-01) -
Trends in combating fake news on social media – a survey
by: Botambu Collins, et al.
Published: (2021-04-01) -
Fake news detection: a survey of evaluation datasets
by: Arianna D’Ulizia, et al.
Published: (2021-06-01)