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An Evaluation System for Credibility of Fake News using Dynamic Relational Networks

This study aims to construct a system to support evaluating credibility of fake news. We proposed a credibility evaluating model using dynamic relationship network which dynamically determines credibility by relative consistency. This credibility evaluation model consists of a <em>conclusion node</em> representing the truth and false of the article and a <em>fact node</em> having information of 5W1H. For evaluation of the crudities model, we evaluated the network using non-fake news and fake news. As a result, it is possible to identify unreliable information from the fact node, and the conclusion node. It was also known found that the trend of the article can be inferred.

The Japanese Society for Artificial Intelligence

JSAI2018

JSAI2018

[1B3-03]An Evaluation System for Credibility of Fake News using Dynamic Relational Networks

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