{"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/abuseanalyzer-abuse-detection-severity-and","title":"AbuseAnalyzer: Abuse Detection, Severity and Target Prediction for Gab Posts","arxiv_id":"2010.00038","date":"2020-09-30","proceeding":"COLING 2020 8","authors":["Mohit Chandra","Ashwin Pathak","Eesha Dutta","Paryul Jain","Manish Gupta","Manish Shrivastava","Ponnurangam Kumaraguru"],"abstract":"While extensive popularity of online social media platforms has made information dissemination faster, it has also resulted in widespread online abuse of different types like hate speech, offensive language, sexist and racist opinions, etc. Detection and curtailment of such abusive content is critical for avoiding its psychological impact on victim communities, and thereby preventing hate crimes. Previous works have focused on classifying user posts into various forms of abusive behavior. But there has hardly been any focus on estimating the severity of abuse and the target. In this paper, we present a first of the kind dataset with 7601 posts from Gab which looks at online abuse from the perspective of presence of abuse, severity and target of abusive behavior. We also propose a system to address these tasks, obtaining an accuracy of ~80% for abuse presence, ~82% for abuse target prediction, and ~65% for abuse severity prediction.","url_abs":"https://arxiv.org/abs/2010.00038v2","url_pdf":"https://arxiv.org/pdf/2010.00038v2.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":"abuseanalyzer-abuse-detection-severity-and","repo_url":"https://github.com/mohit3011/AbuseAnalyzer","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"abuse-detection","task_name":"Abuse Detection"},{"task_slug":"severity-prediction","task_name":"severity prediction"}],"methods":[],"datasets_introduced":[{"slug":"abuseanalyzer-dataset","name":"AbuseAnalyzer Dataset","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2010.00038","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.00038"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/mohit3011/AbuseAnalyzer","reach":null}],"summary":{"unverified":1},"by_repo_kind":{"official":{"samples":1,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"3c49ce3c182ae7ea","entry":"make_bert_input","repo":"mohit3011/AbuseAnalyzer","repo_kind":"official","path":"code_files/BERT_Classifier.py","file_url":"https://github.com/mohit3011/AbuseAnalyzer/blob/HEAD/code_files/BERT_Classifier.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"3c49ce3c182ae7ea"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}