Deploying Fact-Checking Tools to Alleviate Misinformation Promulgation in Twitter Using Machine Learning Techniques
Fact-checking; Fake news; Misinformation; Social media; Twitter
In the present era, the rising portion of our lives is spending interactions online with social media platforms. Thanks to the latest technology adoption as well as smartphones proliferation. Gaining news from the platforms of social media is quicker, easier as well as cheaper in comparison with other traditional media platforms such as T.V and newspapers. Hence, social media is being exploited in order to spread misinformation. The study tends to construct fake corpus that comprises tweets for a product advertisement. The FakeAds corpus objective is to explore the misinformation impact on the advertising and marketing materials for a particular product as well as what kinds of products are targeted mostly on Twitter to draw the consumers attention. Products include cosmetics, fashions, health, electronics, etc. The corpus is varied and novel to the topic (i.e., Twitter role in spreading misinformation in relation to production promotion and advertising) as well as in terms of fine-grained annotations. The guidelines of the annotations were framed through the guidance of domain experts as well as the annotation is done with two domain experts, which results in higher quality annotation, through the agreement rate F-scores as higher as 0.976 using text classification. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes in Networks and Systems, Vol-613 LNNS, pp. 329-346.
Springer Science and Business Media Deutschland GmbH
Sethurajan M.R., CHRIST (Deemed to Be University), Bangalore, India; Natarajan K., CHRIST (Deemed to Be University), Bangalore, India