{"id":"https://openalex.org/W3012011220","doi":"https://doi.org/10.1145/3374664.3379535","title":"On the Impact of Word Representation in Hate Speech and Offensive Language Detection and Explanation","display_name":"On the Impact of Word Representation in Hate Speech and Offensive Language Detection and Explanation","publication_year":2020,"publication_date":"2020-03-13","ids":{"openalex":"https://openalex.org/W3012011220","doi":"https://doi.org/10.1145/3374664.3379535","mag":"3012011220"},"language":"en","primary_location":{"id":"doi:10.1145/3374664.3379535","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3374664.3379535","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth ACM Conference on Data and Application Security and Privacy","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016417047","display_name":"Ruijia Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ruijia (Roger) Hu","raw_affiliation_strings":["Clemson University, Clemson, SC, USA"],"affiliations":[{"raw_affiliation_string":"Clemson University, Clemson, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040884527","display_name":"Wyatt Dorris","orcid":null},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wyatt Dorris","raw_affiliation_strings":["Clemson University &amp; D.W. Daniel High School, Clemson, SC, USA"],"affiliations":[{"raw_affiliation_string":"Clemson University &amp; D.W. Daniel High School, Clemson, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083805756","display_name":"Nishant Vishwamitra","orcid":"https://orcid.org/0000-0002-3728-1921"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nishant Vishwamitra","raw_affiliation_strings":["Clemson University, Clemson, SC, USA"],"affiliations":[{"raw_affiliation_string":"Clemson University, Clemson, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100683466","display_name":"Feng Luo","orcid":"https://orcid.org/0000-0002-4813-2403"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Luo","raw_affiliation_strings":["Clemson University, Clemson, SC, USA"],"affiliations":[{"raw_affiliation_string":"Clemson University, Clemson, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102771033","display_name":"Matthew Costello","orcid":"https://orcid.org/0000-0002-0214-7108"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Costello","raw_affiliation_strings":["Clemson University, Clemson, SC, USA"],"affiliations":[{"raw_affiliation_string":"Clemson University, Clemson, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5016417047"],"corresponding_institution_ids":["https://openalex.org/I8078737"],"apc_list":null,"apc_paid":null,"fwci":0.2651,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.6119795,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"171","last_page":"173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9661999940872192,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9355999827384949,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/offensive","display_name":"Offensive","score":0.9770364761352539},{"id":"https://openalex.org/keywords/pronunciation","display_name":"Pronunciation","score":0.8597819209098816},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7673120498657227},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.610763669013977},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5167590975761414},{"id":"https://openalex.org/keywords/language-identification","display_name":"Language identification","score":0.5138018727302551},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4988064765930176},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.47993093729019165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4476081430912018},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.42788177728652954},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.31864479184150696},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.2144516408443451},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.05842974781990051}],"concepts":[{"id":"https://openalex.org/C176856949","wikidata":"https://www.wikidata.org/wiki/Q2001676","display_name":"Offensive","level":2,"score":0.9770364761352539},{"id":"https://openalex.org/C2780844864","wikidata":"https://www.wikidata.org/wiki/Q184377","display_name":"Pronunciation","level":2,"score":0.8597819209098816},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7673120498657227},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.610763669013977},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5167590975761414},{"id":"https://openalex.org/C129792486","wikidata":"https://www.wikidata.org/wiki/Q1050419","display_name":"Language identification","level":3,"score":0.5138018727302551},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4988064765930176},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.47993093729019165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4476081430912018},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.42788177728652954},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.31864479184150696},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2144516408443451},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.05842974781990051},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3374664.3379535","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3374664.3379535","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth ACM Conference on Data and Application Security and Privacy","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G7265552","display_name":null,"funder_award_id":"1537924","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2250539671","https://openalex.org/W2317579269","https://openalex.org/W2595653137","https://openalex.org/W2785615365","https://openalex.org/W2794585602","https://openalex.org/W2796881724","https://openalex.org/W2807371872","https://openalex.org/W2950577311","https://openalex.org/W2953180101","https://openalex.org/W2954566102","https://openalex.org/W2963464664","https://openalex.org/W2963505958","https://openalex.org/W3012164585","https://openalex.org/W4302032313"],"related_works":["https://openalex.org/W4386566602","https://openalex.org/W3023322875","https://openalex.org/W4200241924","https://openalex.org/W2922580172","https://openalex.org/W3184118381","https://openalex.org/W3117005508","https://openalex.org/W4287064724","https://openalex.org/W3032261270","https://openalex.org/W2955586496","https://openalex.org/W4288413317"],"abstract_inverted_index":{"Online":[0],"hate":[1,32,53,81,127],"speech":[2,33,54,82,128],"and":[3,29,34,50,55,83,107,129,150],"offensive":[4,35,56,84,108,130],"language":[5,36,57,85,109,131],"have":[6,22],"been":[7],"widely":[8],"recognized":[9],"as":[10],"critical":[11],"social":[12],"problems.":[13],"To":[14,94],"defend":[15],"against":[16],"this":[17,72,135],"problem,":[18],"several":[19],"recent":[20],"works":[21],"emerged":[23],"that":[24,140],"focus":[25],"on":[26,113],"the":[27,48,63,66,96,141,148,152,156],"detection":[28,49,90],"explanation":[30,51],"of":[31,52,65,68,80,98,126,155],"using":[37,122],"machine":[38],"learning":[39],"approaches.":[40],"Although":[41],"these":[42],"approaches":[43],"are":[44],"quite":[45],"effective":[46],"in":[47,147],"samples,":[58],"they":[59],"do":[60],"not":[61],"explore":[62],"impact":[64],"representation":[67,79,125],"such":[69],"samples.":[70],"In":[71],"work,":[73],"we":[74,102],"introduce":[75],"a":[76],"novel,":[77],"pronunciation-based":[78,100,124,142],"samples":[86,132],"to":[87,133],"enable":[88],"its":[89],"with":[91],"high":[92],"accuracy.":[93],"demonstrate":[95],"effectiveness":[97],"our":[99,123],"representation,":[101],"extend":[103],"an":[104],"existing":[105,157],"hate-speech":[106],"defense":[110],"model":[111],"based":[112],"deep":[114],"Long":[115],"Short-term":[116],"Memory":[117],"(LSTM)":[118],"neural":[119],"networks":[120],"by":[121],"train":[134],"model.":[136,158],"Our":[137],"work":[138],"finds":[139],"presentation":[143],"significantly":[144],"reduces":[145],"noise":[146],"datasets":[149],"enhances":[151],"overall":[153],"performance":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
