{"id":"https://openalex.org/W2513138008","doi":"https://doi.org/10.1109/access.2016.2594194","title":"A Pattern-Based Approach for Sarcasm Detection on Twitter","display_name":"A Pattern-Based Approach for Sarcasm Detection on Twitter","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2513138008","doi":"https://doi.org/10.1109/access.2016.2594194","mag":"2513138008"},"language":"en","primary_location":{"id":"doi:10.1109/access.2016.2594194","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2016.2594194","pdf_url":null,"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://doi.org/10.1109/access.2016.2594194","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068994330","display_name":"Mondher Bouazizi","orcid":"https://orcid.org/0000-0001-7055-9318"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mondher Bouazizi","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University, Yokohama, Japan","ORCiD"],"raw_orcid":"https://orcid.org/0000-0001-7055-9318","affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016337773","display_name":"Tomoaki Ohtsuki","orcid":"https://orcid.org/0000-0003-3961-1426"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoaki Otsuki Ohtsuki","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University, Yokohama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":29.5813,"has_fulltext":false,"cited_by_count":302,"citation_normalized_percentile":{"value":0.99562522,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"4","issue":null,"first_page":"5477","last_page":"5488"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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":0.9998000264167786,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9894999861717224,"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/T12119","display_name":"Linguistics and Discourse Analysis","score":0.9606000185012817,"subfield":{"id":"https://openalex.org/subfields/1211","display_name":"Philosophy"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sarcasm","display_name":"Sarcasm","score":0.9975444674491882},{"id":"https://openalex.org/keywords/microblogging","display_name":"Microblogging","score":0.8482074737548828},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7707116007804871},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.7392735481262207},{"id":"https://openalex.org/keywords/irony","display_name":"Irony","score":0.6629430651664734},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.553739070892334},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5535302758216858},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4549429714679718},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.44004952907562256},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.42359936237335205},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33252841234207153},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32811933755874634},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.21639567613601685},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.15373048186302185},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.10113778710365295}],"concepts":[{"id":"https://openalex.org/C2776207355","wikidata":"https://www.wikidata.org/wiki/Q191035","display_name":"Sarcasm","level":3,"score":0.9975444674491882},{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.8482074737548828},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7707116007804871},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7392735481262207},{"id":"https://openalex.org/C2779975665","wikidata":"https://www.wikidata.org/wiki/Q131361","display_name":"Irony","level":2,"score":0.6629430651664734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.553739070892334},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5535302758216858},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4549429714679718},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.44004952907562256},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.42359936237335205},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33252841234207153},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32811933755874634},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.21639567613601685},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.15373048186302185},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.10113778710365295},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2016.2594194","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2016.2594194","pdf_url":null,"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:doaj.org/article:6fbd569b51674efe97be7860e3e68c9c","is_oa":true,"landing_page_url":"https://doaj.org/article/6fbd569b51674efe97be7860e3e68c9c","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 4, Pp 5477-5488 (2016)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2016.2594194","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2016.2594194","pdf_url":null,"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":[],"awards":[{"id":"https://openalex.org/G3622748150","display_name":"User Centric Wireless Communications by Traffic Prediction based on Preference Analysis and Integrated Environment Recognition","funder_award_id":"15H04010","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320337513","display_name":"Workforce Development for Teachers and Scientists","ror":"https://ror.org/05msy3529"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W594440611","https://openalex.org/W1842080548","https://openalex.org/W1963704945","https://openalex.org/W1968673961","https://openalex.org/W1969186522","https://openalex.org/W1970491474","https://openalex.org/W1976647541","https://openalex.org/W2000497899","https://openalex.org/W2024011160","https://openalex.org/W2025478229","https://openalex.org/W2038634595","https://openalex.org/W2041400887","https://openalex.org/W2043870592","https://openalex.org/W2053181647","https://openalex.org/W2053968437","https://openalex.org/W2067605006","https://openalex.org/W2070761441","https://openalex.org/W2077018496","https://openalex.org/W2077025666","https://openalex.org/W2098437222","https://openalex.org/W2099653665","https://openalex.org/W2102650424","https://openalex.org/W2107533994","https://openalex.org/W2114661483","https://openalex.org/W2122639307","https://openalex.org/W2132210327","https://openalex.org/W2133990480","https://openalex.org/W2138738738","https://openalex.org/W2140632634","https://openalex.org/W2147964944","https://openalex.org/W2153635508","https://openalex.org/W2165044314","https://openalex.org/W2166706824","https://openalex.org/W2183500697","https://openalex.org/W2223340824","https://openalex.org/W2232443784","https://openalex.org/W2250480277","https://openalex.org/W2250710744","https://openalex.org/W2251124635","https://openalex.org/W2251379416","https://openalex.org/W2251920663","https://openalex.org/W2251958472","https://openalex.org/W2252381721","https://openalex.org/W2263859238","https://openalex.org/W2294058101","https://openalex.org/W2911964244","https://openalex.org/W2951678842","https://openalex.org/W3000293211","https://openalex.org/W6617764921","https://openalex.org/W6638532356","https://openalex.org/W6642572916","https://openalex.org/W6677244998","https://openalex.org/W6680632375","https://openalex.org/W6684364469","https://openalex.org/W6691253234","https://openalex.org/W6691288977","https://openalex.org/W6693457383","https://openalex.org/W6764259099"],"related_works":["https://openalex.org/W3107810543","https://openalex.org/W2346975490","https://openalex.org/W2088249598","https://openalex.org/W4385784095","https://openalex.org/W2593809812","https://openalex.org/W2119977295","https://openalex.org/W2989669783","https://openalex.org/W2468690985","https://openalex.org/W4379932966","https://openalex.org/W3018749573"],"abstract_inverted_index":{"Sarcasm":[0,29],"is":[1,16,43],"a":[2,26,89,97,139],"sophisticated":[3],"form":[4],"of":[5,63,80,109,116,136,149,151,155,171,177],"irony":[6],"widely":[7],"used":[8,18,32],"in":[9],"social":[10,70],"networks":[11],"and":[12,78,82,128,157],"microblogging":[13,67],"websites.":[14],"It":[15],"usually":[17],"to":[19,48,58,75,100,123,142,162],"convey":[20],"implicit":[21],"information":[22],"within":[23],"the":[24,76,113,147,152,163,169,175],"message":[25],"person":[27],"transmits.":[28],"might":[30],"be":[31,55],"for":[33,46,174],"different":[34,114],"purposes,":[35],"such":[36],"as":[37,126],"criticism":[38],"or":[39,69],"mockery.":[40],"However,":[41],"it":[42],"hard":[44],"even":[45],"humans":[47],"recognize.":[49],"Therefore,":[50],"recognizing":[51],"sarcastic":[52,127,178],"statements":[53],"can":[54],"very":[56],"useful":[57],"improve":[59],"automatic":[60],"sentiment":[61],"analysis":[62],"data":[64],"collected":[65],"from":[66],"websites":[68],"networks.":[71],"Sentiment":[72],"Analysis":[73],"refers":[74],"identification":[77],"aggregation":[79],"attitudes":[81],"opinions":[83],"expressed":[84],"by":[85],"Internet":[86],"users":[87],"toward":[88],"specific":[90],"topic.":[91],"In":[92,165],"this":[93],"paper,":[94],"we":[95,118,167],"propose":[96,106],"pattern-based":[98,172],"approach":[99,132],"detect":[101],"sarcasm":[102,117],"on":[103],"Twitter.":[104],"We":[105,120,144],"four":[107],"sets":[108,154],"features":[110,156,173],"that":[111],"cover":[112],"types":[115],"defined.":[119],"use":[121],"those":[122],"classify":[124],"tweets":[125],"non-sarcastic.":[129],"Our":[130],"proposed":[131,153],"reaches":[133],"an":[134],"accuracy":[135],"83.1%":[137],"with":[138],"precision":[140],"equal":[141],"91.1%.":[143],"also":[145],"study":[146],"importance":[148,170],"each":[150],"evaluate":[158],"its":[159],"added":[160],"value":[161],"classification.":[164],"particular,":[166],"emphasize":[168],"detection":[176],"statements.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":48},{"year":2022,"cited_by_count":51},{"year":2021,"cited_by_count":59},{"year":2020,"cited_by_count":37},{"year":2019,"cited_by_count":29},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":12}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
