{"type":"ScholarlyArticle","title":"Hatebusters: A Web Application for Actively Reporting YouTube Hate Speech","authors":[{"name":"Antonios Anagnostou","slug":"antonios-anagnostou","given":"Antonios","family":"Anagnostou","affiliation":"Aristotle University of Thessaloniki , Greece"},{"name":"Ioannis Mollas","slug":"ioannis-mollas","given":"Ioannis","family":"Mollas","affiliation":"Aristotle University of Thessaloniki , Greece"},{"name":"Grigorios Tsoumakas","slug":"grigorios-tsoumakas","given":"Grigorios","family":"Tsoumakas","affiliation":"Aristotle University of Thessaloniki , Greece"}],"abstract":"Hatebusters is a web application for actively reporting YouTube hate speech, aiming to establish an online community of volunteer citizens. Hatebusters searches YouTube for videos with potentially hateful comments, scores their comments with a classifier trained on human-annotated data and presents users those comments with the highest probability of being hate speech. It also employs gamification elements, such as achievements and leaderboards, to drive user engagement.","doi":"10.24963/ijcai.2018/841","url":"https://ijcai.org/proceedings/2018/841","pdf":"https://ijcai.org/proceedings/2018/0841.pdf","markdown":"https://ijcai.org/proceedings/2018/841.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/841","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Demos","track":"Demos","number":841,"pages":{"first":5796,"last":5798},"keywords":["Machine Learning: Data Mining","Natural Language Processing: Text Classification","Machine Learning: Machine Learning"],"videos":[],"references":[{"position":1,"raw":"[Abid et al., 2016] Adnan Abid, Naveed Hussain, Kamran Abid, Farooq Ahmad, Muhammad Shoaib Farooq, Uzma Farooq, Sher Afzal Khan, Yaser Daanial Khan, Muham- mad Azhar Naeem, and Nabeel Sabir. A survey on search results diversification techniques. Neural Computing and Applications, 27(5):1207-1229, 2016.","title":"A survey on search results diversification techniques","authors":"Adnan Abid, Naveed Hussain, Kamran Abid, Farooq Ahmad, Muhammad Shoaib Farooq, Uzma Farooq, Sher Afzal Khan, Yaser Daanial Khan, Muhammad Azhar Naeem, Nabeel Sabir","year":"2016","venue":"Neural Computing and Applications","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Badjatiya et al., 2017] Pinkesh Badjatiya, Shashank Gupta, Manish Gupta, and Vasudeva Varma. Deep learning for hate speech detection in tweets. In Proceedings of the 26th International Conference on World Wide Web Com- panion, WWW '17 Companion, pages 759-760, Republic and Canton of Geneva, Switzerland, 2017. International World Wide Web Conferences Steering Committee.","title":"Deep learning for hate speech detection in tweets","authors":"Badjatiya","year":"2017","venue":"Proceedings of the 26th International Conference on World Wide Web Companion, WWW '17 Companion","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"Burnap and Williams, ] Pete Burnap and Matthew L. Williams. Cyber hate speech on twitter: An application of machine classification and statistical modeling for policy and decision making. Policy & Internet, 7(2):223-242.","title":"Cyber hate speech on twitter: An application of machine classification and statistical modeling for policy and decision making","authors":"Williams Burnap, Pete Burnap, Matthew L Williams","year":null,"venue":"Policy & Internet","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Davidson et al., 2017] Thomas Davidson, Dana Warmsley, Michael Macy, and Ingmar Weber. Automated hate speech detection and the problem of offensive language. In Pro- ceedings of the 11th International AAAI Conference on Web and Social Media, ICWSM '17, pages 512-515, 2017.","title":"Automated hate speech detection and the problem of offensive language","authors":"Thomas Davidson, Dana Warmsley, Michael Macy, Ingmar Weber","year":"2017","venue":"Proceedings of the 11th International AAAI Conference on Web and Social Media, ICWSM '17","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Djuric et al., 2015] Nemanja Djuric, Jing Zhou, Robin Mor- ris, Mihajlo Grbovic, Vladan Radosavljevic, and Narayan Bhamidipati. Hate speech detection with comment embed- dings. In Proceedings of the 24th International Conference on World Wide Web, pages 29-30. ACM, 2015.","title":"Hate speech detection with comment embeddings","authors":"Nemanja Djuric, Jing Zhou, Robin Morris, Mihajlo Grbovic, Vladan Radosavljevic, Narayan Bhamidipati","year":"2015","venue":"Proceedings of the 24th International Conference on World Wide Web","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Gagliardone et al., 2015] Iginio Gagliardone, Danit Gal, Thiago Alves, and Gabriela Martinez. Countering Online Hate Speech. UNESCO Series on Internet Freedom. 2015.","title":"Countering Online Hate Speech","authors":"Iginio Gagliardone, Danit Gal, Thiago Alves, Gabriela Martinez","year":"2015","venue":"UNESCO Series on Internet Freedom","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Gao and Huang, 2017] Lei Gao and Ruihong Huang. De- tecting online hate speech using context aware models. In Proceedings of the International Conference Recent Ad- vances in Natural Language Processing, RANLP 2017, pages 260-266. INCOMA Ltd., 2017.","title":"Detecting online hate speech using context aware models","authors":"Huang ; ] Lei Gao, Ruihong Gao, Huang","year":"2017","venue":"Proceedings of the International Conference Recent Advances in Natural Language Processing","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Gitari et al., 2015] Njagi Dennis Gitari, Zhang Zuping, Hanyurwimfura Damien, and Jun Long. A lexicon-based approach for hate speech detection. International Journal of Multimedia and Ubiquitous Engineering, 10(4):215- 230, 2015.","title":"Njagi Dennis Gitari, Zhang Zuping, Hanyurwimfura Damien, and Jun Long. A lexicon-based approach for hate speech detection","authors":"Gitari","year":"2015","venue":"International Journal of Multimedia and Ubiquitous Engineering","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Lewis, 1995] David D. Lewis. A sequential algorithm for training text classifiers. ACM SIGIR Forum, 29(2):13-19, 1995.","title":"A sequential algorithm for training text classifiers","authors":"David D Lewis","year":"1995","venue":"ACM SIGIR Forum","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Murgia and Warrell, 2017] Madhumita Murgia and Helen Warrell. Why tech companies struggle with hate speech. Financial Times, 2017.","title":"Why tech companies struggle with hate speech","authors":"Warrell Murgia, Madhumita Murgia, Helen Warrell","year":"2017","venue":"Financial Times","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Nobata et al., 2016] Chikashi Nobata, Joel Tetreault, Achint Thomas, Yashar Mehdad, and Yi Chang. Abusive language detection in online user content. In Proceedings of the 25th International Conference on World Wide Web, pages 145-153. International World Wide Web Conferences Steering Committee, 2016.","title":"Abusive language detection in online user content","authors":"Nobata","year":"2016","venue":"Proceedings of the 25th International Conference on World Wide Web","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Park and Fung, 2017] Ji Ho Park and Pascale Fung. One- step and two-step classification for abusive language de- tection on twitter. In Proceedings of the First Workshop on Abusive Language Online, pages 41-45. Association for Computational Linguistics, 2017.","title":"Onestep and two-step classification for abusive language detection on twitter","authors":"Fung ; ] Park, Ho Ji, Pascale Park, Fung","year":"2017","venue":"Proceedings of the First Workshop on Abusive Language Online","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Ross et al., 2016] Björn Ross, Michael Rist, Guillermo Car- bonell, Ben Cabrera, Nils Kurowsky, and Michael Wo- jatzki. Measuring the reliability of hate speech annota- tions: The case of the european refugee crisis. In Michael Beißwenger, Michael Wojatzki, and Torsten Zesch, edi- tors, Proceedings of NLP4CMC III: 3rd Workshop on Nat- ural Language Processing for Computer-Mediated Com- munication, pages 6-9, 2016.","title":"Measuring the reliability of hate speech annotations: The case of the european refugee crisis","authors":"Björn Ross, Michael Rist, Guillermo Carbonell, Ben Cabrera, Nils Kurowsky, Michael Wojatzki","year":"2016","venue":"Proceedings of NLP4CMC III: 3rd Workshop on Natural Language Processing for Computer-Mediated Communication","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Saleem et al., 2016] Haji Mohammad Saleem, Kelly P. Dil- lon, Susan Benesch, and Derek Ruths. A web of hate: Tackling hateful speech in online social spaces. In In pro- ceedings of the 1st workshop on Text Analytics for Cy- bersecurity and Online Safety (TA-COS), collocated with LREC 2016, 2016.","title":"A web of hate: Tackling hateful speech in online social spaces","authors":"Mohammad Haji, Kelly P Saleem, Susan Dillon, Derek Benesch, Ruths","year":"2016","venue":"proceedings of the 1st workshop on Text Analytics for Cybersecurity and Online Safety (TA-COS), collocated with LREC 2016","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Waseem et al., 2017] Zeerak Waseem, Thomas Davidson, Dana Warmsley, and Ingmar Weber. Understanding abuse: A typology of abusive language detection subtasks. arXiv preprint arXiv:1705.09899, 2017.","title":"Understanding abuse: A typology of abusive language detection subtasks","authors":"Waseem","year":"2017","venue":null,"doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}