Hate crime on twitter: Aspect-based sentiment analysis approach
Online media are well-known to be suitable for conveying hate speech. Hateful wording as such involves communications that unlawfully demean any group or person based on certain characteristics, including colour, race, gender, ethnicity, sexual orientation, religion, or nationality. The continuing r...
出版年: | Frontiers in Artificial Intelligence and Applications |
---|---|
第一著者: | Zainuddin N.; Selamat A.; Ibrahim R. |
フォーマット: | Conference paper |
言語: | English |
出版事項: |
IOS Press BV
2019
|
オンライン・アクセス: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082079328&doi=10.3233%2fFAIA190056&partnerID=40&md5=17e1e37d301d4f27b856ed498cb0bc26 |
類似資料
-
Evaluating aspect-based sentiment classification on Twitter hate speech using neural networks and word embedding features
著者:: Zainuddin N.; Selamat A.; Ibrahim R.
出版事項: (2018) -
The Best Malaysian Airline Companies Visualization through Bilingual Twitter Sentiment Analysis: A Machine Learning Classification
著者:: 2-s2.0-85128946535
出版事項: (2022) -
Factors Affecting Crime Rate in Malaysia Using Autoregressive Distributed Lag Modeling Approach
著者:: Zulkiflee N.F.Z.; Borhan N.; Hadrawi M.F.
出版事項: (2022) -
Predicting Mental Health Disorder on Twitter Using Machine Learning Techniques
著者:: 2-s2.0-85175457067
出版事項: (2023) -
Sentiment Analysis on Umrah Packages Review in Malaysia
著者:: Dewi, 等
出版事項: (2024)