CIMTDetect: a community infused matrix-tensor coupled factorization based method for fake news detection

TLDR: In this article, a tensor factorization based method was proposed to encode the news article in a latent embedding space preserving the community structure of echo-chambers in social networks.

Abstract: In this paper, we tackle the problem of fake news detection from social media by exploiting the presence of echo chamber communities (communities sharing same beliefs) that exist within the social network of the users By modeling the echo-chambers as closely-connected communities within the social network, we represent a news article as a 3-mode tensor of the structure - and propose a tensor factorization based method to encode the news article in a latent embedding space preserving the community structure We also propose an extension of the above method, which jointly models the community and content information of the news article through a coupled matrix-tensor factorization framework We empirically demonstrate the efficacy of our method for the task of Fake News Detection over two real-world datasets