Vol.9, No.4, November 2020.                                                                                                                                                                           ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Suspicious Activity Detection of Twitter and Facebook using Sentimental Analysis


Saeed Al Mansoori, Afrah Almansoori, Mohammed Alshamsi, Said A. Salloum, Khaled Shaalan


© 2020 Said A. Salloum, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 9, Issue 4, Pages 1313-1319, ISSN 2217-8309, DOI: 10.18421/TEM94-01, November 2020.


Received: 09 June 2020.

Revised:   22 October 2020.
Accepted: 29 October 2020.
Published: 27 November 2020.




The purpose of this study is to evaluate the criminal behavior on the social media platforms and to classify the gathered data effectively as negative, positive, or neutral in order to identify a suspect. In this study, data was collected from two platforms, Twitter and Facebook, resulting in the creation of two datasets. The following findings have been pointed out from this study: Initially, VADER twitter sentimental analysis showed that out of 5000 tweets 50.8% people shared a neutral opinion, 39.2% shared negative opinion and only 9.9% showed positive opinion. Secondly, on Facebook, the majority of people showed a neutral response which is 55.6%, 38.9% shared positive response and only 5.6% shared negative opinion. Thirdly, the score of sentiments and engagement in every post affects the intensities of sentiments.


Keywords –Criminal behavior, social media platforms, Twitter, Facebook, Part-of-Speech tagging, Valance Aware Dictionary.



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