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Can Machines Learn to Detect Fake News? A Survey Focused on Social Media
|Title:||Can Machines Learn to Detect Fake News? A Survey Focused on Social Media|
|Authors:||Cardoso Durier da Silva, Fernando|
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.
|Rights:||Attribution-NonCommercial-NoDerivatives 4.0 International|
|Appears in Collections:||
Social Movements, Collective Action and Social Technologies|
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