{"id":"https://openalex.org/W4297094757","doi":"https://doi.org/10.1109/access.2022.3210177","title":"PDHS: Pattern-Based Deep Hate Speech Detection With Improved Tweet Representation","display_name":"PDHS: Pattern-Based Deep Hate Speech Detection With Improved Tweet Representation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4297094757","doi":"https://doi.org/10.1109/access.2022.3210177"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3210177","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3210177","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09903616.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09903616.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009039613","display_name":"P. Sharmila","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"P. Sharmila","raw_affiliation_strings":["Thiagarajar College of Engineering, Madurai, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0000-0003-3856-631X","affiliations":[{"raw_affiliation_string":"Thiagarajar College of Engineering, Madurai, Tamil Nadu, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085616371","display_name":"Kalaiarasi Sonai Muthu Anbananthen","orcid":"https://orcid.org/0000-0002-0540-2872"},"institutions":[{"id":"https://openalex.org/I173029219","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33","country_code":"MY","type":"education","lineage":["https://openalex.org/I173029219"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Kalaiarasi Sonai Muthu Anbananthen","raw_affiliation_strings":["Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia"],"raw_orcid":"https://orcid.org/0000-0002-0540-2872","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia","institution_ids":["https://openalex.org/I173029219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007900848","display_name":"Deisy Chelliah","orcid":"https://orcid.org/0000-0001-6140-1682"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deisy Chelliah","raw_affiliation_strings":["Thiagarajar College of Engineering, Madurai, Tamil Nadu, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Thiagarajar College of Engineering, Madurai, Tamil Nadu, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081822748","display_name":"S. Parthasarathy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sudhaman Parthasarathy","raw_affiliation_strings":["Thiagarajar College of Engineering, Madurai, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0000-0001-7439-6878","affiliations":[{"raw_affiliation_string":"Thiagarajar College of Engineering, Madurai, Tamil Nadu, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051606491","display_name":"Subarmaniam Kannan","orcid":"https://orcid.org/0000-0002-0049-4747"},"institutions":[{"id":"https://openalex.org/I173029219","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33","country_code":"MY","type":"education","lineage":["https://openalex.org/I173029219"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Subarmaniam Kannan","raw_affiliation_strings":["Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia","institution_ids":["https://openalex.org/I173029219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.8035,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.87373668,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"10","issue":null,"first_page":"105366","last_page":"105376"},"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":0.9492999911308289,"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/computer-science","display_name":"Computer science","score":0.8285830020904541},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5993740558624268},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.593177855014801},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5247657299041748},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5240914225578308},{"id":"https://openalex.org/keywords/voice-activity-detection","display_name":"Voice activity detection","score":0.4944186210632324},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.4942965507507324},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4601675868034363},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.45752960443496704},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.44833144545555115},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40254050493240356},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35442453622817993},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.3375130891799927}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8285830020904541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5993740558624268},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.593177855014801},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5247657299041748},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5240914225578308},{"id":"https://openalex.org/C204201278","wikidata":"https://www.wikidata.org/wiki/Q1332614","display_name":"Voice activity detection","level":3,"score":0.4944186210632324},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.4942965507507324},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4601675868034363},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.45752960443496704},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.44833144545555115},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40254050493240356},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35442453622817993},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.3375130891799927},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2022.3210177","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3210177","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09903616.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:shdl.mmu.edu.my:10597","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196753","display_name":"Siti Hasmah Digital Library-MMU Institutiona Repository (Multimedia University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173029219","host_organization_name":"Multimedia University","host_organization_lineage":["https://openalex.org/I173029219"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"NonPeerReviewed"},{"id":"pmh:oai:doaj.org/article:748630f690704159be8e5dfa2a372408","is_oa":true,"landing_page_url":"https://doaj.org/article/748630f690704159be8e5dfa2a372408","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 105366-105376 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3210177","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3210177","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09903616.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7200000286102295}],"awards":[{"id":"https://openalex.org/G1870557850","display_name":null,"funder_award_id":"MMUE/210038","funder_id":"https://openalex.org/F4320326578","funder_display_name":"Telekom Malaysia Berhad"}],"funders":[{"id":"https://openalex.org/F4320326578","display_name":"Telekom Malaysia Berhad","ror":"https://ror.org/00s3fdw25"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4297094757.pdf","grobid_xml":"https://content.openalex.org/works/W4297094757.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W2556605533","https://openalex.org/W2612186323","https://openalex.org/W2745850770","https://openalex.org/W2797669327","https://openalex.org/W2803013062","https://openalex.org/W2806872289","https://openalex.org/W2808079449","https://openalex.org/W2887782043","https://openalex.org/W2889086200","https://openalex.org/W2889612797","https://openalex.org/W2892137778","https://openalex.org/W2896457183","https://openalex.org/W2898401058","https://openalex.org/W2901224794","https://openalex.org/W2906846845","https://openalex.org/W2911752708","https://openalex.org/W2914097099","https://openalex.org/W2937643694","https://openalex.org/W2954858824","https://openalex.org/W2962932155","https://openalex.org/W2963337756","https://openalex.org/W2998535576","https://openalex.org/W2998964503","https://openalex.org/W3000204454","https://openalex.org/W3004829062","https://openalex.org/W3013577339","https://openalex.org/W3016441316","https://openalex.org/W3016463114","https://openalex.org/W3045081979","https://openalex.org/W3095278059","https://openalex.org/W3126181281","https://openalex.org/W3156333129","https://openalex.org/W3201426476","https://openalex.org/W3211926874","https://openalex.org/W4226058218","https://openalex.org/W4238481634","https://openalex.org/W6682691769"],"related_works":["https://openalex.org/W642007152","https://openalex.org/W2401827384","https://openalex.org/W4294771049","https://openalex.org/W2052688117","https://openalex.org/W2552102772","https://openalex.org/W1523214805","https://openalex.org/W2168417340","https://openalex.org/W4229451372","https://openalex.org/W2113211312","https://openalex.org/W1510046822"],"abstract_inverted_index":{"Automatic":[0],"hate":[1,31,40,71],"speech":[2,41,72],"identification":[3],"in":[4],"unstructured":[5],"Twitter":[6,147],"is":[7,106,119],"significantly":[8],"more":[9],"difficult":[10],"to":[11,36,66,124,153],"analyze,":[12],"posing":[13],"a":[14,43,53,55,74,78,126],"significant":[15],"challenge.":[16],"Existing":[17],"models":[18],"heavily":[19],"depend":[20],"on":[21,146],"feature":[22],"engineering,":[23],"which":[24],"increases":[25],"the":[26,68,85,98,121,132,155],"time":[27,160],"complexity":[28],"of":[29,70,83,104,117],"detecting":[30],"speech.":[32],"This":[33],"work":[34],"aims":[35],"classify":[37],"and":[38,140,161],"detect":[39,67],"using":[42,73,110],"linguistic":[44],"pattern-based":[45],"approach":[46],"as":[47],"pre-trained":[48],"transformer":[49],"language":[50],"models.":[51],"As":[52],"result,":[54],"novel":[56],"Pattern-based":[57],"Deep":[58],"Hate":[59],"Speech":[60],"(PDHS)":[61],"detection":[62],"model":[63,88,130],"was":[64],"proposed":[65,129],"presence":[69],"cross-attention":[75],"encoder":[76],"with":[77,135,157],"dual-level":[79],"attention":[80,92],"mechanism.":[81],"Instead":[82],"concatenating":[84],"features,":[86],"our":[87],"computes":[89],"dot":[90],"product":[91],"for":[93],"better":[94],"representation":[95],"by":[96],"reducing":[97],"irrelevant":[99],"features.":[100],"The":[101,114,143],"first":[102],"level":[103,116],"Attention":[105,118],"extracting":[107,120],"aspect":[108],"terms":[109],"predefined":[111],"parts-of-speech":[112,138],"tagging.":[113],"second":[115],"sentiment":[122],"polarity":[123],"form":[125],"pattern.":[127],"Our":[128],"trains":[131],"extracted":[133],"patterns":[134],"term":[136],"frequency,":[137],"tag,":[139],"Sentiment":[141],"Scores.":[142],"experimental":[144],"results":[145],"Dataset":[148],"can":[149],"learn":[150],"effective":[151],"features":[152],"enhance":[154],"performance":[156],"minimum":[158],"training":[159],"attained":[162],"88%F1Score.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}