Hate Speech Detection: Performance Based upon a Novel Feature Detection
Hate speech is abusive or stereotyping speech against a group of people, based on characteristics such as race, religion, sexual orientation, and gender. Internet and social media have made it possible to spread hatred easily, fast, and anonymously. The large scale of data produced through social me...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Engineering Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4591/31/1/87 |
| _version_ | 1797594969373933568 |
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| author | Saugata Bose |
| author_facet | Saugata Bose |
| author_sort | Saugata Bose |
| collection | DOAJ |
| description | Hate speech is abusive or stereotyping speech against a group of people, based on characteristics such as race, religion, sexual orientation, and gender. Internet and social media have made it possible to spread hatred easily, fast, and anonymously. The large scale of data produced through social media platforms requires the development of effective automatic methods to detect such content. Hate speech detection in short text on social media has become an active research topic in recent years, as it differs from the traditional information retrieval for documents. My research is to develop a method to effectively detect hate speech based on deep learning techniques. I have proposed a novel feature based on the lexicon of short text. Experiments have shown that proposed deep-neural-network-based models improve the performance when a novel feature combines with CNN and SVM. |
| first_indexed | 2024-03-11T02:31:13Z |
| format | Article |
| id | doaj.art-e195ff117485466f8a189761dc53dac3 |
| institution | Directory Open Access Journal |
| issn | 2673-4591 |
| language | English |
| last_indexed | 2024-03-11T02:31:13Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj.art-e195ff117485466f8a189761dc53dac32023-11-18T10:16:43ZengMDPI AGEngineering Proceedings2673-45912022-12-013118710.3390/ASEC2022-13788Hate Speech Detection: Performance Based upon a Novel Feature DetectionSaugata Bose0School of Computing and Information Technology, Faculty of Science and Engineering and Information Sciences, University of Wollongong, Wollongong, NSW 2500, AustraliaHate speech is abusive or stereotyping speech against a group of people, based on characteristics such as race, religion, sexual orientation, and gender. Internet and social media have made it possible to spread hatred easily, fast, and anonymously. The large scale of data produced through social media platforms requires the development of effective automatic methods to detect such content. Hate speech detection in short text on social media has become an active research topic in recent years, as it differs from the traditional information retrieval for documents. My research is to develop a method to effectively detect hate speech based on deep learning techniques. I have proposed a novel feature based on the lexicon of short text. Experiments have shown that proposed deep-neural-network-based models improve the performance when a novel feature combines with CNN and SVM.https://www.mdpi.com/2673-4591/31/1/87hate speechCNNSVMfeature detection |
| spellingShingle | Saugata Bose Hate Speech Detection: Performance Based upon a Novel Feature Detection Engineering Proceedings hate speech CNN SVM feature detection |
| title | Hate Speech Detection: Performance Based upon a Novel Feature Detection |
| title_full | Hate Speech Detection: Performance Based upon a Novel Feature Detection |
| title_fullStr | Hate Speech Detection: Performance Based upon a Novel Feature Detection |
| title_full_unstemmed | Hate Speech Detection: Performance Based upon a Novel Feature Detection |
| title_short | Hate Speech Detection: Performance Based upon a Novel Feature Detection |
| title_sort | hate speech detection performance based upon a novel feature detection |
| topic | hate speech CNN SVM feature detection |
| url | https://www.mdpi.com/2673-4591/31/1/87 |
| work_keys_str_mv | AT saugatabose hatespeechdetectionperformancebaseduponanovelfeaturedetection |