FANG

DOI DOI DOI Web Site Research Data 1 Citations 1 References Open Access

Bibliographic Information

Other Title
  • leveraging social context for fake news detection using graph representation

Search this article

Description

<jats:p>We propose Factual News Graph (FANG), a novel graphical social context representation and learning framework for fake news detection. Unlike previous contextual models that have targeted performance, our focus is on representation learning. Compared to transductive models, FANG is scalable in training as it does not have to maintain the social entities involved in the propagation of other news and is efficient at inference time, without the need to reprocess the entire graph. Our experimental results show that FANG is better at capturing the social context into a high-fidelity representation, compared to recent graphical and nongraphical models. In particular, FANG yields significant improvements for the task of fake news detection and is robust in the case of limited training data. We further demonstrate that the representations learned by FANG generalize to related tasks, such as predicting the factuality of reporting of a news medium.</jats:p>

Journal

Citations (1)*help

See more

References(1)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top