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A deep learning approach for detecting the behavior of people having personality disorders towards Covid-19 from Twitter

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posted on 23.09.2021, 12:42 by Mourad Ellouze, Seifeddine Mechti, Moez KrichenMoez Krichen, vinayakumar Rvinayakumar R, Lamia Hadrich Belguith
This paper proposes an architecture taking advantage of artificial intelligence and text mining techniques in order to: (i) detect paranoid people by classifying their set of tweets into two classes (Paranoid/not-Paranoid), (ii) ensure the surveillance of these people by classifying their tweets about Covid-19 into two classes (person with normal behavior, person with inappropriate behavior). These objectives are achieved using an approach that takes advantage of different information related to the textual part, user and tweets for features selection task and deep neural network for the classification task. We obtained as an F-score rate 70% for the detection of paranoid people and 73% for the detection of the behavior of these people towards Covid-19. The obtained results are motivating and encouraging researchers to improve them given the interest and the importance of this research axis.

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Email Address of Submitting Author

vinayakumarr77@gmail.com

ORCID of Submitting Author

0000-0001-6873-6469

Submitting Author's Institution

Prince Mohammad bin Fahd University

Submitting Author's Country

Saudi Arabia

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