dc.contributor.author |
Watawana, R.K |
|
dc.date.accessioned |
2022-03-14T04:19:51Z |
|
dc.date.available |
2022-03-14T04:19:51Z |
|
dc.date.issued |
2021 |
|
dc.identifier.citation |
"Watawana, R.K (2021) PREDICTION OF CYBERBULLYING USING DEEP LEARNING. BSc. Dissertation Informatics Institute of Technology" |
en_US |
dc.identifier.issn |
2017165 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/937 |
|
dc.description.abstract |
"
Cyberbullying has become a critical issue in the today society. Cyberbullying victims
throughout the world increasing from day by day as this whole system is based on online
activities. The negative impact given by the cyberbullying incident initially start with the
self-confidence of the victim and gradually went through some stages and end with the
final stage of suicide. Suicide is the final and the most critical condition of cyberbullying.
The worst case is most of the cyberbullying victims is young adults. Still today a proper
technology solution has not been identified to minimize the worldwide issue of
cyberbullying.
This Sinhala language cyberbullying detection system mainly focused on the young adults
who faced cyberbullying. This tool can be used for Twitter social media platform. The
tweet can be classified as the cyberbullying or not. If the tweet detected as cyberbullying
the victim is given some solutions as some motivational books and the psychological
doctors. Parent of the victim or the cyberbullying victim can use this tool, since this is a
user-friendly tool that can be used by young person. This tool is a timely need for the
modern society.
The main intention of this project is to stop suicide cases of young adults and teenagers
due to the cyberbullying incidents." |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
Text Classification |
en_US |
dc.subject |
Natural Language Processing |
en_US |
dc.subject |
Sinhala Cyberbullying Detection |
en_US |
dc.title |
PREDICTION OF CYBERBULLYING USING DEEP LEARNING |
en_US |
dc.type |
Thesis |
en_US |