The Role of Text Mining in Mitigating the Threats from Fake News and Misinformation in Times of Corona

被引:6
|
作者
Englmeier, Kurt [1 ]
机构
[1] Schmalkalden Univ Appl Sci, D-98574 Schmalkalden, Germany
关键词
Fake News; Plausibilty Check; Named Entity Recognition; Bag of Words; Fact Retrieval; Text Mining;
D O I
10.1016/j.procs.2021.01.115
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Misinformation can be a threat to our democracies, societies, and economies. The most dangerous consequence of misinformation is mistrust. It threatens the reciprocal respect and esteem in our societies. Fake news as such are not the problem as long as we can detect misinformation. Fake news rest on misinformation. This, in turn, means we that have to check the veracity of the information or advice of whoever is addressing us. This paper presents a prototype of the Contexter system developed at our university that demonstrates the design of a fact checking system to detect fake news and misinformation. The system enables the definition of blueprints for the presentation of facts in texts. With the abstract representation of facts, Contexter looks up similar facts in order to detect fake news and misinformation. The data sources used for this article are publications on Covid-19 from different newspapers and from Twitter. (C) 2021 The Authors. Published by Elsevier B.V.
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页码:149 / 156
页数:8
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