{"id":"https://openalex.org/W4206128876","doi":"https://doi.org/10.1109/bigdata52589.2021.9671427","title":"ConOffense: Multi-modal multitask Contrastive learning for offensive content identification","display_name":"ConOffense: Multi-modal multitask Contrastive learning for offensive content identification","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4206128876","doi":"https://doi.org/10.1109/bigdata52589.2021.9671427"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671427","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671427","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","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/A5082912094","display_name":"Debaditya Shome","orcid":"https://orcid.org/0000-0001-9168-0379"},"institutions":[{"id":"https://openalex.org/I67357951","display_name":"KIIT University","ror":"https://ror.org/00k8zt527","country_code":"IN","type":"education","lineage":["https://openalex.org/I67357951"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Debaditya Shome","raw_affiliation_strings":["School of Electronics Engineering, KIIT University, Odisha, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering, KIIT University, Odisha, India","institution_ids":["https://openalex.org/I67357951"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022613820","display_name":"T. Kar","orcid":"https://orcid.org/0000-0001-9020-3626"},"institutions":[{"id":"https://openalex.org/I67357951","display_name":"KIIT University","ror":"https://ror.org/00k8zt527","country_code":"IN","type":"education","lineage":["https://openalex.org/I67357951"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"T. Kar","raw_affiliation_strings":["School of Electronics Engineering, KIIT University, Odisha, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering, KIIT University, Odisha, India","institution_ids":["https://openalex.org/I67357951"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I67357951"],"apc_list":null,"apc_paid":null,"fwci":0.761,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.75397412,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4524","last_page":"4529"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9329000115394592,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10485","display_name":"Bullying, Victimization, and Aggression","score":0.928600013256073,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/offensive","display_name":"Offensive","score":0.9508912563323975},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7622756361961365},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5772191286087036},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5699033737182617},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5676574110984802},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5668246746063232},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5658894777297974},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.548933744430542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5454918742179871},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.48721665143966675},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42187440395355225},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4060624837875366},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3598853349685669},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.12901738286018372},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10136014223098755}],"concepts":[{"id":"https://openalex.org/C176856949","wikidata":"https://www.wikidata.org/wiki/Q2001676","display_name":"Offensive","level":2,"score":0.9508912563323975},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7622756361961365},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5772191286087036},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5699033737182617},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5676574110984802},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5668246746063232},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5658894777297974},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.548933744430542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5454918742179871},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.48721665143966675},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42187440395355225},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4060624837875366},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3598853349685669},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.12901738286018372},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10136014223098755},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671427","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671427","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1975423998","https://openalex.org/W2194775991","https://openalex.org/W2473555522","https://openalex.org/W2595653137","https://openalex.org/W2740168486","https://openalex.org/W2953692061","https://openalex.org/W2973089652","https://openalex.org/W3009899658","https://openalex.org/W3087777115","https://openalex.org/W3090114880","https://openalex.org/W3093890791","https://openalex.org/W3155638757","https://openalex.org/W3169973903","https://openalex.org/W3173171735","https://openalex.org/W3194975438","https://openalex.org/W3198548129","https://openalex.org/W3198943295","https://openalex.org/W4287257982","https://openalex.org/W4287812705","https://openalex.org/W6631190155","https://openalex.org/W6776700526","https://openalex.org/W6783961830","https://openalex.org/W6792161730","https://openalex.org/W6794142944","https://openalex.org/W6801054480"],"related_works":["https://openalex.org/W4310034804","https://openalex.org/W4213225422","https://openalex.org/W3044458868","https://openalex.org/W4250304930","https://openalex.org/W4289656111","https://openalex.org/W2922457425","https://openalex.org/W2567271240","https://openalex.org/W2788487394","https://openalex.org/W2989980351","https://openalex.org/W3002526821"],"abstract_inverted_index":{"Hateful":[0],"or":[1],"offensive":[2,55,135],"content":[3,91],"has":[4,47,61],"been":[5,48,62],"increasingly":[6],"common":[7,87],"on":[8,63,81,92,137,167,194],"social":[9,41,138],"media":[10,42,139],"platforms":[11],"in":[12,50,77,96],"recent":[13],"years,":[14],"and":[15,143,150],"the":[16,37,51,59,75,97,115,148,159,168,188,195],"problem":[17],"is":[18,22,85],"now":[19],"widespread.":[20],"There":[21],"a":[23,124,154],"pressing":[24],"need":[25],"for":[26,30,133,162],"effective":[27],"automatic":[28],"solutions":[29],"detecting":[31],"such":[32],"content,":[33,56],"especially":[34],"due":[35],"to":[36,88,101,111,157],"gigantic":[38],"size":[39],"of":[40,54,58,174,182],"data.":[43],"Although":[44],"significant":[45],"progress":[46],"made":[49],"automated":[52],"identification":[53],"most":[57],"focus":[60],"only":[64],"using":[65],"textual":[66,144],"information.":[67,145],"It":[68],"can":[69],"be":[70,109],"easily":[71],"noticed":[72],"that":[73],"with":[74,114,153],"rise":[76],"visual":[78,142,151],"information":[79],"shared":[80],"these":[82],"platforms,":[83],"it":[84],"quite":[86],"have":[89],"hateful":[90,117],"images":[93],"rather":[94],"than":[95],"associated":[98],"text.":[99],"Due":[100],"this,":[102],"present":[103],"day":[104],"unimodal":[105],"text-based":[106],"methods":[107],"won\u2019t":[108],"able":[110],"cope":[112],"up":[113],"multimodal":[116,126],"content.":[118],"In":[119],"this":[120],"paper,":[121],"we":[122],"propose":[123],"novel":[125],"neural":[127],"network":[128],"powered":[129],"by":[130],"contrastive":[131],"learning":[132],"identifying":[134],"posts":[136],"utilizing":[140],"both":[141],"We":[146],"design":[147],"text":[149],"encoders":[152],"lightweight":[155],"architecture":[156],"make":[158],"solution":[160],"efficient":[161],"real":[163],"world":[164],"use.":[165],"Evaluation":[166],"MMHS150K":[169],"dataset":[170],"shows":[171],"state-of-the-art":[172],"performance":[173],"82.6":[175],"percent":[176,185],"test":[177],"accuracy,":[178],"making":[179],"an":[180],"improvement":[181],"approximately":[183],"+14.1":[184],"accuracy":[186],"over":[187],"previous":[189],"best":[190],"performing":[191],"benchmark":[192],"model":[193],"dataset.":[196]},"counts_by_year":[{"year":2024,"cited_by_count":6}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}