Can Machines Learn to Detect Fake News? A Survey Focused on Social Media
Files
Date
2019-01-08
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Narrator
Transcriber
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
Ending Page
Alternative Title
Abstract
Through a systematic literature review method, in this work we searched classical electronic libraries in order to find the most recent papers related to fake news detection on social medias. Our target is mapping the state of art of fake news detection, defining fake news and finding the most useful machine learning technique for doing so.
We concluded that the most used method for automatic fake news detection is not just one classical machine learning technique, but instead a amalgamation of classic techniques coordinated by a neural network.
We also identified a need for a domain ontology that would unify the different terminology and definitions of the fake news domain. This lack of consensual information may mislead opinions and conclusions.
Description
Keywords
Social Movements, Collective Action and Social Technologies, Digital and Social Media, Automated, Detection, Fake, Misinformation, News
Citation
Extent
8 pages
Format
Geographic Location
Time Period
Related To
Proceedings of the 52nd Hawaii International Conference on System Sciences
Related To (URI)
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.