{"id":"https://openalex.org/W4200310290","doi":"https://doi.org/10.1155/2021/2529984","title":"A Generalized Method for Sentiment Analysis across Different Sources","display_name":"A Generalized Method for Sentiment Analysis across Different Sources","publication_year":2021,"publication_date":"2021-12-18","ids":{"openalex":"https://openalex.org/W4200310290","doi":"https://doi.org/10.1155/2021/2529984"},"language":"en","primary_location":{"id":"doi:10.1155/2021/2529984","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2529984","pdf_url":"https://downloads.hindawi.com/journals/acisc/2021/2529984.pdf","source":{"id":"https://openalex.org/S30680879","display_name":"Applied Computational Intelligence and Soft Computing","issn_l":"1687-9724","issn":["1687-9724","1687-9732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computational Intelligence and Soft Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://downloads.hindawi.com/journals/acisc/2021/2529984.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038519736","display_name":"Abubakar M. Ashir","orcid":"https://orcid.org/0000-0003-4009-8463"},"institutions":[{"id":"https://openalex.org/I908820301","display_name":"Tishk International University","ror":"https://ror.org/03pbhyy22","country_code":"IQ","type":"education","lineage":["https://openalex.org/I908820301"]}],"countries":["IQ"],"is_corresponding":true,"raw_author_name":"Abubakar M. Ashir","raw_affiliation_strings":["Department of Computer Engineering, Tishk International University, Erbil, Iraq"],"raw_orcid":"https://orcid.org/0000-0003-4009-8463","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Tishk International University, Erbil, Iraq","institution_ids":["https://openalex.org/I908820301"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5038519736"],"corresponding_institution_ids":["https://openalex.org/I908820301"],"apc_list":{"value":900,"currency":"USD","value_usd":900},"apc_paid":{"value":900,"currency":"USD","value_usd":900},"fwci":1.2594,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.84268359,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"2021","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.996999979019165,"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":0.9968000054359436,"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":0.8584998846054077},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7641224265098572},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7074909210205078},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.6993075609207153},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6094973683357239},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5324761867523193},{"id":"https://openalex.org/keywords/lexical-analysis","display_name":"Lexical analysis","score":0.526027500629425},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5253476500511169},{"id":"https://openalex.org/keywords/part-of-speech","display_name":"Part of speech","score":0.49178746342658997},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4915789067745209},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.48041343688964844},{"id":"https://openalex.org/keywords/stop-words","display_name":"Stop words","score":0.418759822845459},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3912505805492401}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8584998846054077},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7641224265098572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7074909210205078},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.6993075609207153},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6094973683357239},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5324761867523193},{"id":"https://openalex.org/C176982825","wikidata":"https://www.wikidata.org/wiki/Q835922","display_name":"Lexical analysis","level":2,"score":0.526027500629425},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5253476500511169},{"id":"https://openalex.org/C123406163","wikidata":"https://www.wikidata.org/wiki/Q82042","display_name":"Part of speech","level":2,"score":0.49178746342658997},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4915789067745209},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.48041343688964844},{"id":"https://openalex.org/C188338183","wikidata":"https://www.wikidata.org/wiki/Q80735","display_name":"Stop words","level":3,"score":0.418759822845459},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3912505805492401}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2021/2529984","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2529984","pdf_url":"https://downloads.hindawi.com/journals/acisc/2021/2529984.pdf","source":{"id":"https://openalex.org/S30680879","display_name":"Applied Computational Intelligence and Soft Computing","issn_l":"1687-9724","issn":["1687-9724","1687-9732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computational Intelligence and Soft Computing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8e019f777bc046c59b8c2ab8382ae8e5","is_oa":true,"landing_page_url":"https://doaj.org/article/8e019f777bc046c59b8c2ab8382ae8e5","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":"Applied Computational Intelligence and Soft Computing, Vol 2021 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2021/2529984","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2529984","pdf_url":"https://downloads.hindawi.com/journals/acisc/2021/2529984.pdf","source":{"id":"https://openalex.org/S30680879","display_name":"Applied Computational Intelligence and Soft Computing","issn_l":"1687-9724","issn":["1687-9724","1687-9732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computational Intelligence and Soft Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4200310290.pdf","grobid_xml":"https://content.openalex.org/works/W4200310290.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W193524605","https://openalex.org/W1614298861","https://openalex.org/W1987425720","https://openalex.org/W2003504193","https://openalex.org/W2079823081","https://openalex.org/W2081580037","https://openalex.org/W2099813784","https://openalex.org/W2113459411","https://openalex.org/W2143017621","https://openalex.org/W2194578903","https://openalex.org/W2216627755","https://openalex.org/W2467206427","https://openalex.org/W2489406233","https://openalex.org/W2743699808","https://openalex.org/W2884491530","https://openalex.org/W2999286261","https://openalex.org/W3006588007","https://openalex.org/W3153073204","https://openalex.org/W6676984168"],"related_works":["https://openalex.org/W2888662092","https://openalex.org/W3205826705","https://openalex.org/W2903394456","https://openalex.org/W2902285665","https://openalex.org/W3119550360","https://openalex.org/W2975174210","https://openalex.org/W4200238620","https://openalex.org/W2244029015","https://openalex.org/W2287843335","https://openalex.org/W3158961892"],"abstract_inverted_index":{"Sentiment":[0],"analysis":[1,89],"is":[2,79,145],"widely":[3],"used":[4,180],"in":[5,18,26,29,235,291],"a":[6,74,111,154,171,175,183],"variety":[7],"of":[8,21,50,103,132,149,212,287],"applications":[9],"such":[10,129],"as":[11,130,244],"online":[12,67],"opinion":[13],"gathering":[14],"for":[15,34,62,114,139,174],"policy":[16],"directives":[17],"government,":[19],"monitoring":[20],"customers,":[22],"and":[23,31,38,76,105,122,137,156,194,218,263,267,280],"staff":[24],"satisfactions":[25],"corporate":[27],"bodies,":[28],"politics":[30],"security":[32],"structures":[33],"public":[35],"tension":[36],"monitoring,":[37],"so":[39],"on.":[40],"In":[41,71],"recent":[42],"times,":[43],"the":[44,108,245,285,288],"field":[45],"met":[46],"with":[47,58,82,90,100,151,200,209,293],"new":[48,53],"set":[49],"challenges":[51],"where":[52],"algorithms":[54],"have":[55],"to":[56,86,181],"contend":[57],"highly":[59],"unstructured":[60],"sources":[61,101,220],"sentiment":[63,88],"expressions":[64],"emanating":[65],"from":[66,162,250],"social":[68],"media":[69],"fora.":[70],"this":[72],"study,":[73],"rule":[75],"lexical-based":[77],"procedure":[78],"proposed":[80,188,289],"together":[81,169],"unsupervised":[83,236],"machine":[84,184,202],"learning":[85,185,233,237],"implement":[87],"an":[91],"improved":[92,207],"generalization":[93,213],"ability":[94],"across":[95,215],"different":[96,201],"sources.":[97],"To":[98],"deal":[99,211],"devoid":[102],"syntactic":[104],"grammatical":[106],"structure,":[107],"approach":[109,290],"incorporates":[110],"ruled-based":[112],"technique":[113],"emoticon":[115],"detection,":[116],"word":[117,241],"contraction":[118],"expansion,":[119],"noise":[120],"removal,":[121],"lexicon-based":[123],"text":[124,144,177],"preprocessing":[125],"using":[126,170,240],"lexical":[127,230],"features":[128,159,166,231],"part":[131],"speech":[133],"(POS),":[134],"stop":[135],"words,":[136],"lemmatization":[138],"local":[140],"context":[141],"analysis.":[142],"A":[143],"broken":[146],"into":[147],"number":[148],"tokens":[150],"each":[152,163],"representing":[153],"sentence":[155],"then":[157],"lexicon-dependent":[158],"are":[160,167],"extracted":[161],"token.":[164],"The":[165,187,224],"merged":[168],"combining":[172,189],"function":[173],"given":[176],"before":[178],"being":[179],"train":[182],"classifier.":[186],"functions":[190],"leverage":[191],"on":[192],"averaging":[193],"information":[195],"gain":[196],"concepts.":[197],"Experimental":[198],"results":[199,249],"leaning":[203],"classifiers":[204],"indicate":[205],"that":[206,227],"performance":[208],"great":[210],"capacity":[214],"both":[216],"structured":[217],"nonstructured":[219],"can":[221],"be":[222],"realized.":[223],"finding":[225],"shows":[226],"carefully":[228],"designed":[229],"reinforce":[232],"process":[234],"more":[238],"than":[239],"embeddings":[242],"alone":[243],"features.":[246],"Obtained":[247],"experimental":[248],"movie":[251],"review":[252],"dataset":[253],"(recall":[254,271],"=":[255,258,261,265,272,275,278,282],"74.9%,":[256],"precision":[257,274],"70.9%,":[259],"F1-score":[260,277],"72.9%,":[262],"accuracy":[264,281],"72.0%)":[266],"twitter":[268],"samples\u2019":[269],"datasets":[270],"93.4%,":[273],"89.5%,":[276],"91.4%,":[279],"91.1%)":[283],"show":[284],"efficacy":[286],"comparison":[292],"other":[294],"state-of-the-art":[295],"research":[296],"studies.":[297]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}