Pulse Brain · Growing Health Evidence Index
Peer-reviewed

CYBER BULLYING SCRUTINY FOR WOMEN SECURITY IN SOCIAL MEDIA

M Hossain, M Rahman, M Islam, M Hossain, L Mubassara, M Towhid, S Sultana, A Anik, M Salwa, M Khan, J Thavil, V Durdhawale, P Elake, W Akram, M Jain, C Hemalatha, P Sumathy, P Shiva, R Mugundhan, S Rakesh, Prasath, Dhruvil Parikh, Pallavi Kapoor, Shital Karnani, Sudhir Kadam, Priyanka Das, Asit Das, M Pramod, C Bhaskar, K Shikha, L Chao, C Xing, Y Zhang, C Zhang, N Shrestha, T Barik, C Parnin, Ramadhan Rizki, Setyadi, Arif Istikmal, Irawan Indra, D Charunangia, Sabir Singh, Ali, P Biradar

International Research Journal of Modernization in Engineering Technology and Science · 2023

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Summary

In recent year, the number of users in social media has been increased multiple times when compared to the past. The bullying like abuse word, aggressive text or posting some unwanted messages are common in social media. So, the women feel unsecured in the society. Although a lot of techniques and methodology has been raised, but still the problem remains same. The major problem is the abuse word can be eliminated by the mean of report to the particular social media like Twitter, Facebook etc. In this methodology the unwanted message can be truncated in between the sender and receiver itself using the machine learning techniques. Sentiment analysis is a challenge of the Natural Language Processing (NLP), text analytics and computational linguistics which also helps in identifying the bad t

Subject
Measurement methods & nutrient profiling
Source type
Peer-reviewed study
System type
Other
DOI
10.56726/irjmets34819
Catalogue ID
SNmojj21t6-kcmane
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