Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/59713

Can Machines Learn to Detect Fake News? A Survey Focused on Social Media

File Size Format  
0273.pdf 170.4 kB Adobe PDF View/Open

Item Summary

Title:Can Machines Learn to Detect Fake News? A Survey Focused on Social Media
Authors:Cardoso Durier da Silva, Fernando
Vieira, Rafael
Garcia, Ana Cristina
Keywords:Social Movements, Collective Action and Social Technologies
Digital and Social Media
Automated, Detection, Fake, Misinformation, News
Date Issued:08 Jan 2019
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.
Pages/Duration:8 pages
URI:http://hdl.handle.net/10125/59713
ISBN:978-0-9981331-2-6
DOI:10.24251/HICSS.2019.332
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Social Movements, Collective Action and Social Technologies


Please email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.

This item is licensed under a Creative Commons License Creative Commons