A HYBRID APPROACH TO FAKE NEWS DETECTION ON SOCIAL MEDIA
DOI:
https://doi.org/10.4314/njt.372.1678Keywords:
Fake news detection, Human decision making, Machine decision makingAbstract
Fake news has grown tremendously in recent times and this growth has had a great impact on how we make a number of sensitive decisions daily including becomes our President. There have been a wide range of solutions developed to help humans distinguish between fake and real news however, the solutions rely on either a machine-based approach or a human-based approach to detection. Research in the fields of computer science, artificial intelligence and psychology research has shown the limitations in both approaches. Based on these research findings, this paper proposes a hybrid model for detecting fake news on social media using a combination of both the human-based and machine-based detection approaches.
Downloads
Published
Issue
Section
License
The contents of the articles are the sole opinion of the author(s) and not of NIJOTECH.
NIJOTECH allows open access for distribution of the published articles in any media so long as whole (not part) of articles are distributed.
A copyright and statement of originality documents will need to be filled out clearly and signed prior to publication of an accepted article. The Copyright form can be downloaded from http://nijotech.com/downloads/COPYRIGHT%20FORM.pdf while the Statement of Originality is in http://nijotech.com/downloads/Statement%20of%20Originality.pdf
For articles that were developed from funded research, a clear acknowledgement of such support should be mentioned in the article with relevant references. Authors are expected to provide complete information on the sponsorship and intellectual property rights of the article together with all exceptions.
It is forbidden to publish the same research report in more than one journal.

