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Truth Detection Algorithm in Social Media Tweets Using Similarity Measures

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Part of the Algorithms for Intelligent Systems book series (AIS)


In the social media environment, many tweets are posted by users. It is amongst the way of living with social media culture in this era. Internet and Online Media are an important part of communication these days. Sometimes fake news can create a lot of issues that may not be expected by the users. Therefore, it is regulated by cyber-crime authorities to regulate the news and general rules are created by social media websites. This makes it necessary for a proper truth detection algorithm. In this paper, a java implementation of a modified Jaccard Algorithm is applied which then classifies news from the dataset as true or false. The dataset is initially classified on sentiments which are done through the Stanford CoreNLP library in Java. The results show good accuracy for truth detection. This is used in big data truth discovery algorithm to prevent misinformation spread.


  • Social media
  • Truth detection
  • Tweet sentiment
  • Parallel credibility
  • NLP
  • Data analytics
  • Jaccard similarity

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  • DOI: 10.1007/978-981-16-6460-1_18
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Correspondence to Vishesh Gupta .

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Gupta, V., G.Vadivu (2022). Truth Detection Algorithm in Social Media Tweets Using Similarity Measures. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Bestak, R. (eds) Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore.

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