{"id":"https://openalex.org/W4309744786","doi":"https://doi.org/10.1080/01969722.2022.2146849","title":"An Optimized Crossover Framework for Social Media Sentiment Analysis","display_name":"An Optimized Crossover Framework for Social Media Sentiment Analysis","publication_year":2022,"publication_date":"2022-11-23","ids":{"openalex":"https://openalex.org/W4309744786","doi":"https://doi.org/10.1080/01969722.2022.2146849"},"language":"en","primary_location":{"id":"doi:10.1080/01969722.2022.2146849","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01969722.2022.2146849","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybernetics and Systems","raw_type":"journal-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/A5070074088","display_name":"Surender Singh Samant","orcid":"https://orcid.org/0000-0001-8619-3779"},"institutions":[{"id":"https://openalex.org/I60054993","display_name":"Graphic Era University","ror":"https://ror.org/03wqgqd89","country_code":"IN","type":"education","lineage":["https://openalex.org/I60054993"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Surender Singh Samant","raw_affiliation_strings":["Department of Computer Science and Engineering, Graphic Era (Deemed to be University), Dehradun, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Graphic Era (Deemed to be University), Dehradun, India","institution_ids":["https://openalex.org/I60054993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112419932","display_name":"Vijay Singh","orcid":null},"institutions":[{"id":"https://openalex.org/I60054993","display_name":"Graphic Era University","ror":"https://ror.org/03wqgqd89","country_code":"IN","type":"education","lineage":["https://openalex.org/I60054993"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vijay Singh","raw_affiliation_strings":["Department of Computer Science and Engineering, Graphic Era (Deemed to be University), Dehradun, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Graphic Era (Deemed to be University), Dehradun, India","institution_ids":["https://openalex.org/I60054993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060891564","display_name":"Arun Chauhan","orcid":null},"institutions":[{"id":"https://openalex.org/I60054993","display_name":"Graphic Era University","ror":"https://ror.org/03wqgqd89","country_code":"IN","type":"education","lineage":["https://openalex.org/I60054993"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arun Chauhan","raw_affiliation_strings":["Department of Computer Science and Engineering, Graphic Era (Deemed to be University), Dehradun, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Graphic Era (Deemed to be University), Dehradun, India","institution_ids":["https://openalex.org/I60054993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083262971","display_name":"Jagadish Dasarahalli Narasimaiah","orcid":null},"institutions":[{"id":"https://openalex.org/I4210152718","display_name":"Indian Institute of Technology Dharwad","ror":"https://ror.org/0509djg30","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210152718"]},{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]},{"id":"https://openalex.org/I4387153068","display_name":"Indian Institute of Information Technology Dharwad","ror":"https://ror.org/0237jt454","country_code":null,"type":"education","lineage":["https://openalex.org/I4387153068"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jagadish Dasarahalli Narasimaiah","raw_affiliation_strings":["Department of Electronics and Communication Engineering, IIIT Dharwad, Dharwad, India"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, IIIT Dharwad, Dharwad, India","institution_ids":["https://openalex.org/I4210152718","https://openalex.org/I119939252","https://openalex.org/I4387153068"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5070074088"],"corresponding_institution_ids":["https://openalex.org/I60054993"],"apc_list":null,"apc_paid":null,"fwci":0.7954,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77087665,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"55","issue":"8","first_page":"2140","last_page":"2168"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9830999970436096,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9624000191688538,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7980209589004517},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.7086246609687805},{"id":"https://openalex.org/keywords/lexical-analysis","display_name":"Lexical analysis","score":0.6999843120574951},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6707045435905457},{"id":"https://openalex.org/keywords/tf\u2013idf","display_name":"tf\u2013idf","score":0.644950270652771},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.587278425693512},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5611894130706787},{"id":"https://openalex.org/keywords/bigram","display_name":"Bigram","score":0.5543500781059265},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.44948750734329224},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3807666003704071},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35473382472991943},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.28080010414123535},{"id":"https://openalex.org/keywords/trigram","display_name":"Trigram","score":0.1038009524345398}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7980209589004517},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.7086246609687805},{"id":"https://openalex.org/C176982825","wikidata":"https://www.wikidata.org/wiki/Q835922","display_name":"Lexical analysis","level":2,"score":0.6999843120574951},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6707045435905457},{"id":"https://openalex.org/C81758059","wikidata":"https://www.wikidata.org/wiki/Q796584","display_name":"tf\u2013idf","level":3,"score":0.644950270652771},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.587278425693512},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5611894130706787},{"id":"https://openalex.org/C108757681","wikidata":"https://www.wikidata.org/wiki/Q2773912","display_name":"Bigram","level":3,"score":0.5543500781059265},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.44948750734329224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3807666003704071},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35473382472991943},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.28080010414123535},{"id":"https://openalex.org/C137546455","wikidata":"https://www.wikidata.org/wiki/Q3213474","display_name":"Trigram","level":2,"score":0.1038009524345398},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/01969722.2022.2146849","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01969722.2022.2146849","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybernetics and Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1970827139","https://openalex.org/W2286994843","https://openalex.org/W2417173111","https://openalex.org/W2594056497","https://openalex.org/W2738417325","https://openalex.org/W2748437478","https://openalex.org/W2781487490","https://openalex.org/W2906531487","https://openalex.org/W2913898221","https://openalex.org/W2926264417","https://openalex.org/W2941002834","https://openalex.org/W2945712752","https://openalex.org/W2966614482","https://openalex.org/W2982156295","https://openalex.org/W2989752582","https://openalex.org/W2995797250","https://openalex.org/W2995987488","https://openalex.org/W2997254516","https://openalex.org/W3000739907","https://openalex.org/W3004511036","https://openalex.org/W3010618814","https://openalex.org/W3014413883","https://openalex.org/W3015647315","https://openalex.org/W3021126976","https://openalex.org/W3032886784","https://openalex.org/W3035056367","https://openalex.org/W3035269559","https://openalex.org/W3039918539","https://openalex.org/W3044872781","https://openalex.org/W3100754052","https://openalex.org/W3127541405","https://openalex.org/W3135449691","https://openalex.org/W3154265922","https://openalex.org/W3195189374","https://openalex.org/W3196661916","https://openalex.org/W3206133953","https://openalex.org/W3214618715","https://openalex.org/W3215822937","https://openalex.org/W4200171677","https://openalex.org/W4205598820","https://openalex.org/W4206506030","https://openalex.org/W4224035554"],"related_works":["https://openalex.org/W2563096758","https://openalex.org/W3192794374","https://openalex.org/W4362613237","https://openalex.org/W4293525103","https://openalex.org/W3184989376","https://openalex.org/W4386053843","https://openalex.org/W3158004940","https://openalex.org/W2345184372","https://openalex.org/W3200179079","https://openalex.org/W3010923102"],"abstract_inverted_index":{"Using":[0],"deep":[1],"learning,":[2,124],"a":[3,192],"new":[4],"sentiment":[5,38,185],"analysis":[6],"model":[7,187],"is":[8,17,106,149,188],"designed":[9],"in":[10],"our":[11],"article.":[12],"The":[13,26,40,78,92,126,169,183],"original":[14],"data":[15],"(input)":[16],"first":[18],"pre-processed":[19,58],"by":[20,88,108,191],"stemming,":[21],"stop-word":[22],"removal,":[23],"and":[24,37,51,116],"tokenization.":[25],"projected":[27],"technique":[28],"includes":[29],"4":[30],"phases:":[31],"\"pre-processing,":[32],"feature":[33,35],"extraction,":[34],"selection,":[36],"classification.\"":[39],"characteristics":[41],"\u201cBigram-BoW":[42],"(B-BoW),":[43],"Threshold":[44],"Term":[45],"Frequency-Inverse":[46],"Document":[47],"Frequency":[48],"(T-TFIDF),":[49],"Unigram,":[50],"N-Gram\u201d":[52],"are":[53,132,177],"then":[54,96,189],"retrieved":[55],"from":[56],"the":[57,61,66,71,100,110,136,140,153,156,161,165,175],"data.":[59],"Utilizing":[60],"self-improved":[62,145],"Honey":[63,80,146],"Badger":[64,81,147],"Algorithm,":[65],"best":[67],"features":[68,73,131],"out":[69],"of":[70,155,164],"chosen":[72,76,130],"will":[74,95,172],"be":[75,97],"(SI-HBA).":[77,168],"basic":[79],"Algorithm":[82,148],"(HBA)":[83],"has":[84],"been":[85],"conceptually":[86],"improved":[87],"this":[89],"SI-HBA":[90,127],"model.":[91],"review":[93],"classification":[94,162,186],"conducted":[98],"via":[99],"proposed":[101,184],"optimized":[102,111,141],"crossover":[103,142],"framework,":[104],"which":[105],"constructed":[107],"hybridizing":[109],"Bi-Long":[112],"Short-Term":[113],"Memory":[114],"(Bi-LSTM)":[115],"Deep":[117],"Belief":[118],"Network":[119],"(DBN)":[120],"trained":[121],"with":[122],"Transfer":[123],"respectively.":[125],"model\u2019s":[128],"optimally":[129],"used":[133,150],"to":[134,151,159],"train":[135],"hybrid":[137],"classifier":[138,158],"within":[139],"architecture.":[143],"A":[144],"fine-tune":[152],"weight":[154],"Bi-LSTM":[157],"improve":[160],"performance":[163],"gathered":[166],"reviews":[167,176],"final":[170],"results":[171],"indicate":[173],"whether":[174],"mostly":[178],"good,":[179],"negative,":[180],"or":[181],"neutral.":[182],"validated":[190],"comparison":[193],"analysis.":[194]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}