{"id":"https://openalex.org/W4296886579","doi":"https://doi.org/10.1109/inista55318.2022.9894143","title":"An Improved Hybrid Method for Sentiment Analysis","display_name":"An Improved Hybrid Method for Sentiment Analysis","publication_year":2022,"publication_date":"2022-08-08","ids":{"openalex":"https://openalex.org/W4296886579","doi":"https://doi.org/10.1109/inista55318.2022.9894143"},"language":"en","primary_location":{"id":"doi:10.1109/inista55318.2022.9894143","is_oa":false,"landing_page_url":"https://doi.org/10.1109/inista55318.2022.9894143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5072395577","display_name":"Sarsabene Hammi","orcid":"https://orcid.org/0000-0001-9041-5960"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Sarsabene Hammi","raw_affiliation_strings":["Mir@cl, FSEGS,Computer Science,Sfax,Tunisia","Computer Science, Mir@cl, FSEGS, Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mir@cl, FSEGS,Computer Science,Sfax,Tunisia","institution_ids":["https://openalex.org/I142899784"]},{"raw_affiliation_string":"Computer Science, Mir@cl, FSEGS, Sfax, Tunisia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058663795","display_name":"Souha Mezghani Hammami","orcid":null},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Souha Mezghani Hammami","raw_affiliation_strings":["Mir@cl, FSEGS,Computer Science,Sfax,Tunisia","Computer Science, Mir@cl, FSEGS, Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mir@cl, FSEGS,Computer Science,Sfax,Tunisia","institution_ids":["https://openalex.org/I142899784"]},{"raw_affiliation_string":"Computer Science, Mir@cl, FSEGS, Sfax, Tunisia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001984598","display_name":"Lamia Hadrich Belguith","orcid":"https://orcid.org/0000-0002-4868-657X"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Lamia Hadrich Belguith","raw_affiliation_strings":["Mir@cl, FSEGS,Computer Science,Sfax,Tunisia","Computer Science, Mir@cl, FSEGS, Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mir@cl, FSEGS,Computer Science,Sfax,Tunisia","institution_ids":["https://openalex.org/I142899784"]},{"raw_affiliation_string":"Computer Science, Mir@cl, FSEGS, Sfax, Tunisia","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142899784"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9973999857902527,"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/T10028","display_name":"Topic Modeling","score":0.9778000116348267,"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":0.8085110187530518},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.779536783695221},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.710784375667572},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6158362627029419},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5749989748001099},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5699697732925415},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5662497282028198},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5521621704101562},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5382354855537415},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5303434133529663},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46104520559310913},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4503249228000641},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.42718902230262756},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.420870840549469},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2439357340335846}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8085110187530518},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.779536783695221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.710784375667572},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6158362627029419},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5749989748001099},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5699697732925415},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5662497282028198},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5521621704101562},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5382354855537415},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5303434133529663},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46104520559310913},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4503249228000641},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.42718902230262756},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.420870840549469},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2439357340335846},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C1491633281","wikidata":"https://www.wikidata.org/wiki/Q7868","display_name":"Cell","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/inista55318.2022.9894143","is_oa":false,"landing_page_url":"https://doi.org/10.1109/inista55318.2022.9894143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1924689489","https://openalex.org/W2084046180","https://openalex.org/W2112422413","https://openalex.org/W2474565205","https://openalex.org/W2569656908","https://openalex.org/W2612769033","https://openalex.org/W2792883466","https://openalex.org/W2935044269","https://openalex.org/W3188562288","https://openalex.org/W4205617840","https://openalex.org/W6731714126","https://openalex.org/W6799389447"],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2400337198","https://openalex.org/W2354902965","https://openalex.org/W2596247554","https://openalex.org/W4301373556","https://openalex.org/W1984947604","https://openalex.org/W3021501837","https://openalex.org/W2379140333"],"abstract_inverted_index":{"In":[0,53],"recent":[1],"years,":[2],"the":[3,26,31,34,54,59,81,88,100,132],"sentiment":[4],"analysis":[5],"task":[6],"has":[7],"received":[8],"great":[9],"attention":[10],"from":[11,131],"communities.":[12],"To":[13,117],"fulfill":[14],"this":[15,20],"task,":[16],"we":[17,57,98,121],"proposed":[18],"in":[19,129],"paper":[21],"a":[22,72,92,123],"hybrid":[23],"method":[24,36,47,66],"for":[25],"French":[27,130],"language":[28],"that":[29],"combines":[30],"strengths":[32],"of":[33,39,50,74,94,126,142],"lexical-based":[35,65],"and":[37,42,91,110],"those":[38],"deep":[40,111],"learning-based":[41,44],"machine":[43,103],"methods.":[45],"This":[46],"consists":[48],"principally":[49],"two":[51],"steps.":[52],"first":[55],"step,":[56],"annotate":[58],"learning":[60,104,112],"dataset":[61,124],"using":[62,102],"an":[63,139],"enhanced":[64],"which":[67],"is":[68],"mainly":[69],"based":[70],"on":[71],"set":[73,93],"new":[75],"rules.":[76],"These":[77],"rules":[78],"improve":[79],"significantly":[80],"polarity":[82],"detection":[83],"by":[84],"taking":[85],"into":[86],"account":[87],"contextual":[89],"information":[90],"specific":[95],"words.":[96],"Then,":[97],"classify":[99],"reviews":[101,128],"(Na\u00efve":[105],"Bayes,":[106],"Support":[107],"Vector":[108],"Machine)":[109],"(Long":[113],"Short-Term":[114],"Memory)":[115],"algorithms.":[116],"realize":[118],"our":[119],"method,":[120],"collected":[122],"composed":[125],"7000":[127],"online":[133],"purchase":[134],"site":[135],"Amazon.fr.":[136],"We":[137],"obtained":[138],"overall":[140],"rate":[141],"F-measure":[143],"equal":[144],"to":[145],"96,14%.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}