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A computer screen reading 'Fake news'

PI: Thomas Lukasiewicz

Department: Computer Science

Fake news items on the Web influence many people and have started to become a huge problem in important political and economic decisions, such as Brexit and the U.S. presidential elections. For this reason, there is major interest from governments and web companies alike (e.g. social networks, web search companies, and online newspapers) to detect and remove fake news. Clearly, this cannot be done manually anymore, e.g. there are more than a billion daily active users on Facebook. It is thus only natural to think about developing artificial intelligence technologies to detect fake online news.

As a step towards a spinout company developing such a technology, based on Prof Lukasiewicz’s own previous research and on developed technologies, the goal of this project is (i) to create a proof-of-concept demonstrator for computing a fake news score, denoted FakeNewsRank, for facts, articles, authors, and websites, which measures their likelihood of being fake, and (ii) to identify any still existing key gaps or challenges. In addition to this, the project will also produce (iii) datasets (for two different domains, e.g. politics and the economy) of sample blog messages and news articles, containing true and fake facts, along with their authors and web addresses, and (iv) background knowledge graphs underlying these datasets.

More specifically, the demonstrator will be based on Prof Lukasiewicz and his group’s deep-learning-based system for extracting facts from plain text, which extracts facts relative to a background knowledge graph from plain natural language text on a web page. Furthermore, the project will also be based on the group’s deep-learning-based system for ontology reasoning, which will be used to determine the likelihood of truth of an extracted fact relative to the underlying background knowledge graph. The FakeNewsRank computed by the demonstrator will be based on this likelihood of extracted facts and on other parameters.

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