Suspicious Activity Detection of Twitter and Facebook using Sentimental Analysis
Suspicious Activity Detection of Twitter and Facebook using Sentimental Analysis
Author(s): Saeed Al Mansoori, Afrah Almansoori, Mohammed Alshamsi, Said Salloum, Khaled ShaalanSubject(s): ICT Information and Communications Technologies
Published by: UIKTEN - Association for Information Communication Technology Education and Science
Keywords: Criminal behavior; social media platforms; Twitter; Facebook; Part-of-Speech tagging; Valance Aware Dictionary;
Summary/Abstract: 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.
Journal: TEM Journal
- Issue Year: 9/2020
- Issue No: 4
- Page Range: 1313-1319
- Page Count: 7
- Language: English
