dc.contributor.author |
Dikwatta, U. |
|
dc.contributor.author |
Fernando, T.G.I. |
|
dc.date.accessioned |
2022-02-08T04:10:35Z |
|
dc.date.available |
2022-02-08T04:10:35Z |
|
dc.date.issued |
2019-11-30 |
|
dc.identifier.citation |
Dikwatta, U.. Fernando, T.G.I. (2019). "Violence Detection in Social Media-Review", Vidyodaya Journal of Science Vol. 22 No. 02 (2019) 7-16 |
en_US |
dc.identifier.uri |
http://dr.lib.sjp.ac.lk/handle/123456789/10147 |
|
dc.description.abstract |
Social media has become a vital part of humans’ day to day life. Different users engage with
social media differently. With the increased usage of social media, many researchers have investigated
different aspects of social media. Many examples in the recent past show, content in the social media
can generate violence in the user community. Violence in social media can be categorised into
aggregation in comments, cyber-bullying and incidents like protests, murders. Identifying violent
content in social media is a challenging task: social media posts contain both the visual and text as well
as these posts may contain hidden meaning according to the users’ context and other background
information. This paper summarizes the different social media violent categories and existing methods to
detect the violent content. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Vidyodaya Journal of Science |
en_US |
dc.subject |
Machine learning, natural language processing, violence, social media, convolution neural network |
en_US |
dc.title |
Violence Detection in Social Media-Review |
en_US |
dc.type |
Article |
en_US |