{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/detecting-online-hate-speech-using-context","title":"Detecting Online Hate Speech Using Context Aware Models","arxiv_id":"1710.07395","date":"2017-10-20","proceeding":"RANLP 2017 9","authors":["Lei Gao","Ruihong Huang"],"abstract":"In the wake of a polarizing election, the cyber world is laden with hate\nspeech. Context accompanying a hate speech text is useful for identifying hate\nspeech, which however has been largely overlooked in existing datasets and hate\nspeech detection models. In this paper, we provide an annotated corpus of hate\nspeech with context information well kept. Then we propose two types of hate\nspeech detection models that incorporate context information, a logistic\nregression model with context features and a neural network model with learning\ncomponents for context. Our evaluation shows that both models outperform a\nstrong baseline by around 3% to 4% in F1 score and combining these two models\nfurther improve the performance by another 7% in F1 score.","url_abs":"http://arxiv.org/abs/1710.07395v2","url_pdf":"http://arxiv.org/pdf/1710.07395v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"detecting-online-hate-speech-using-context","repo_url":"https://github.com/sjtuprog/fox-news-comments","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"detecting-online-hate-speech-using-context","repo_url":"https://github.com/causalate-mitigates-bias/causal-ate-mitigates-bias","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"hate-speech-detection","task_name":"Hate Speech Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1710.07395","atlas_url":"https://app.syntology.ai/?focus=1710.07395","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}