Text Analytics Solutions for the Control of Fake News: Materials and Methods

Emeka Ogbuju, Taiwo Abiodun, Francisca Oladipo


The increase in the rate of internet and social media use has given rise to a lot of fake news and misinformation available online. The internet and social media have made information and communications flow to be faster and easier. On the other hand, the internet and social media have also jeopardized the authenticity of the news that is being sent online, as it has given people the opportunity to intentionally spread fake news. This has caused a lot of social and national damage with destructive impacts. Hence, there is a need to apply data mining and text analytic techniques in the detection of fake news across news agencies that operate online. Literature has shown that the use of data mining and text analytic techniques can play important role in both the detection of fake news and the blockage of it. The leading data mining and text analytic techniques used in fake news detection are described in this paper by answering three (3) research questions from papers between 2017 to 2022 alongside recommendations for applications for newsagents. The result presents fourteen (14) techniques and twenty (20) state of the arts datasets for fake news research.

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