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PREDICTION OF CYBERBULLYING USING DEEP LEARNING

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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


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