{"id":"https://openalex.org/W2897465368","doi":"https://doi.org/10.1109/indicon.2017.8487712","title":"Hyperbolic Feature-based Sarcasm Detection in Tweets: A Machine Learning Approach","display_name":"Hyperbolic Feature-based Sarcasm Detection in Tweets: A Machine Learning Approach","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2897465368","doi":"https://doi.org/10.1109/indicon.2017.8487712","mag":"2897465368"},"language":"en","primary_location":{"id":"doi:10.1109/indicon.2017.8487712","doi":"https://doi.org/10.1109/indicon.2017.8487712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indicon.2017.8487712","pdf_url":null,"source":{"id":"https://openalex.org/S4306418634","display_name":"IEEE India Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2017 14th IEEE India Council International Conference (INDICON)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5051494356","display_name":"Santosh Kumar Bharti","orcid":"https://orcid.org/0000-0002-0627-6433","observed_orcids":["https://orcid.org/0000-0002-0627-6433"]},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Santosh Kumar Bharti","raw_affiliation_strings":["Computer Science & Engineering, National Institute of Technology, Rourkela, Odisha, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, National Institute of Technology, Rourkela, Odisha, India","institution_ids":["https://openalex.org/I16292982"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Reddy Naidu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reddy Naidu","raw_affiliation_strings":["Computer Science & Engineering, ANITS Engineering College, Visakhapatnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, ANITS Engineering College, Visakhapatnam","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011961429","display_name":"Korra Sathya Babu","orcid":"https://orcid.org/0000-0002-5963-5735","observed_orcids":["https://orcid.org/0000-0002-5963-5735"]},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Korra Sathya Babu","raw_affiliation_strings":["Computer Science & Engineering, National Institute of Technology, Rourkela, Odisha, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, National Institute of Technology, Rourkela, Odisha, India","institution_ids":["https://openalex.org/I16292982"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3299,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.5313959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9994999766349792,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9994999766349792,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":9.999999747378752e-05,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sarcasm-detection","display_name":"sarcasm detection","score":1.0},{"id":"https://openalex.org/keywords/intensifiers","display_name":"intensifiers","score":0.953000009059906},{"id":"https://openalex.org/keywords/interjections","display_name":"interjections","score":0.9980000257492065},{"id":"https://openalex.org/keywords/twitter","display_name":"Twitter","score":0.765999972820282},{"id":"https://openalex.org/keywords/social-media-text","display_name":"social media text","score":0.7160000205039978},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"sentiment analysis","score":0.75},{"id":"https://openalex.org/keywords/classifiers","display_name":"machine learning classifiers","score":0.6029999852180481}],"concepts":[{"id":"https://openalex.org/C2776207355","wikidata":"https://www.wikidata.org/wiki/Q191035","display_name":"Sarcasm","level":3,"score":0.9810527563095093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7735127210617065},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7190022468566895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6940060257911682},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.6373550891876221},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6306531429290771},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5582526922225952},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5349693894386292},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5105277299880981},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5077760815620422},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11685186624526978},{"id":"https://openalex.org/C2779975665","wikidata":"https://www.wikidata.org/wiki/Q131361","display_name":"Irony","level":2,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"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:10.1109/indicon.2017.8487712","doi":"https://doi.org/10.1109/indicon.2017.8487712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indicon.2017.8487712","pdf_url":null,"source":{"id":"https://openalex.org/S4306418634","display_name":"IEEE India Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2017 14th IEEE India Council International Conference (INDICON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W872253517","https://openalex.org/W1550206324","https://openalex.org/W1632114991","https://openalex.org/W1930624869","https://openalex.org/W1988790447","https://openalex.org/W1990596909","https://openalex.org/W2108646579","https://openalex.org/W2114661483","https://openalex.org/W2128420091","https://openalex.org/W2232443784","https://openalex.org/W2250247764","https://openalex.org/W2250710744","https://openalex.org/W2251920663","https://openalex.org/W2263859238","https://openalex.org/W2294058101","https://openalex.org/W2472594302","https://openalex.org/W2489370933","https://openalex.org/W2513138008","https://openalex.org/W2579285186","https://openalex.org/W2609876222","https://openalex.org/W2787894218","https://openalex.org/W4211186029","https://openalex.org/W4239510810","https://openalex.org/W4248437541"],"related_works":["https://openalex.org/W2609876222","https://openalex.org/W4322577796","https://openalex.org/W3041285871","https://openalex.org/W4392785199","https://openalex.org/W7171616195","https://openalex.org/W4391493648","https://openalex.org/W7220519653","https://openalex.org/W3178147764","https://openalex.org/W4312466329","https://openalex.org/W2513138008"],"abstract_inverted_index":{"In":[0,66],"recent":[1],"times,":[2],"sarcasm":[3,20,72],"analysis":[4],"has":[5,55],"been":[6],"one":[7],"of":[8,19,44,83,87,92,126],"the":[9,30,42,88,93],"toughest":[10],"challenges":[11],"in":[12,41],"Natural":[13],"Language":[14],"Processing":[15],"(NLP).":[16],"The":[17,79,90,120],"property":[18],"that":[21],"makes":[22],"it":[23],"difficult":[24],"to":[25],"analyze":[26],"and":[27,35,85,118,131,138],"detect":[28],"is":[29,77,96],"gap":[31],"between":[32],"its":[33],"literal":[34],"intended":[36],"meaning.":[37],"Detecting":[38],"sarcastic":[39],"sentiment":[40],"domain":[43],"social":[45],"media":[46],"such":[47],"as":[48,60],"Facebook,":[49],"Twitter,":[50],"online":[51],"blogs,":[52],"reviews,":[53],"etc.":[54],"become":[56],"an":[57,123],"essential":[58],"task":[59],"they":[61],"influence":[62],"every":[63],"business":[64],"organization.":[65],"this":[67],"article,":[68],"a":[69],"hyperbolic":[70,80],"feature-based":[71],"detector":[73],"for":[74],"Twitter":[75],"data":[76],"proposed.":[78],"features":[81],"consist":[82],"intensifiers":[84],"interjections":[86],"text.":[89],"performance":[91],"proposed":[94],"system":[95,121],"analyzed":[97],"using":[98,133],"several":[99],"standard":[100],"machine":[101],"learning":[102],"approaches":[103],"namely,":[104],"Naive":[105],"Bayes":[106],"(NB),":[107],"Decision":[108],"Tree":[109],"(DT),":[110],"Support":[111],"Vector":[112],"Machine":[113],"(SVM),":[114],"Random":[115],"Forest":[116],"(RF),":[117],"AdaBoost.":[119],"attains":[122],"accuracy":[124],"(%)":[125],"75.12,":[127],"80.27,":[128],"80.67,":[129],"80.79,":[130],"80.07":[132],"NB,":[134],"DT,":[135],"SVM,":[136],"RF,":[137],"AdaBoost":[139],"respectively.":[140]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2018-10-26T00:00:00"}