{"id":"https://openalex.org/W3200344301","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533870","title":"The Case Against Sentiment Analysis for Natural Text","display_name":"The Case Against Sentiment Analysis for Natural Text","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200344301","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533870","mag":"3200344301"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533870","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5064401481","display_name":"Shamoon Siddiqui","orcid":null},"institutions":[{"id":"https://openalex.org/I44265643","display_name":"Rowan University","ror":"https://ror.org/049v69k10","country_code":"US","type":"education","lineage":["https://openalex.org/I44265643"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shamoon Siddiqui","raw_affiliation_strings":["Rowan University, New Jersey, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rowan University, New Jersey, USA","institution_ids":["https://openalex.org/I44265643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045996251","display_name":"Ghulam Rasool","orcid":"https://orcid.org/0000-0001-8551-0090"},"institutions":[{"id":"https://openalex.org/I44265643","display_name":"Rowan University","ror":"https://ror.org/049v69k10","country_code":"US","type":"education","lineage":["https://openalex.org/I44265643"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ghulam Rasool","raw_affiliation_strings":["Rowan University, New Jersey, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rowan University, New Jersey, USA","institution_ids":["https://openalex.org/I44265643"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036207748","display_name":"Ravi P. Ramachandran","orcid":"https://orcid.org/0000-0003-0011-4561"},"institutions":[{"id":"https://openalex.org/I44265643","display_name":"Rowan University","ror":"https://ror.org/049v69k10","country_code":"US","type":"education","lineage":["https://openalex.org/I44265643"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ravi P. Ramachandran","raw_affiliation_strings":["Rowan University, New Jersey, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rowan University, New Jersey, USA","institution_ids":["https://openalex.org/I44265643"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I44265643"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"30","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":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/T10028","display_name":"Topic Modeling","score":0.9991999864578247,"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":0.9966999888420105,"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":0.679566502571106},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5355057716369629},{"id":"https://openalex.org/keywords/natural","display_name":"Natural (archaeology)","score":0.49395233392715454},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.444192498922348},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35990995168685913},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.34464892745018005},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07042565941810608}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.679566502571106},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5355057716369629},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.49395233392715454},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.444192498922348},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35990995168685913},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.34464892745018005},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07042565941810608},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533870","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8199999928474426,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G4170240606","display_name":null,"funder_award_id":"P200A180055","funder_id":"https://openalex.org/F4320306106","funder_display_name":"U.S. Department of Education"}],"funders":[{"id":"https://openalex.org/F4320306106","display_name":"U.S. Department of Education","ror":"https://ror.org/021adze67"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2024490156","https://openalex.org/W2084046180","https://openalex.org/W2111281748","https://openalex.org/W2113459411","https://openalex.org/W2145482038","https://openalex.org/W2148506018","https://openalex.org/W2166706824","https://openalex.org/W2170240176","https://openalex.org/W2199803028","https://openalex.org/W2251939518","https://openalex.org/W2401379394","https://openalex.org/W2571253853","https://openalex.org/W2624457496","https://openalex.org/W2783233804","https://openalex.org/W2807374657","https://openalex.org/W2894868452","https://openalex.org/W2896457183","https://openalex.org/W2963012544","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2970597249","https://openalex.org/W3005991624","https://openalex.org/W3046950317","https://openalex.org/W3102444842","https://openalex.org/W3118781290","https://openalex.org/W4307979480","https://openalex.org/W4385245566","https://openalex.org/W6685053522","https://openalex.org/W6687724439","https://openalex.org/W6755207826","https://openalex.org/W6755247350","https://openalex.org/W6763701032","https://openalex.org/W6774440824"],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2596247554","https://openalex.org/W3132372214","https://openalex.org/W4224284088","https://openalex.org/W4286571989","https://openalex.org/W2765903680","https://openalex.org/W4317653575","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Natural":[0],"language":[1,80],"processing":[2],"is":[3,22,28,143],"a":[4,130],"broad":[5],"field":[6,55],"that":[7,13,23,135,137],"encompasses":[8],"several":[9,20],"sub-tasks.":[10],"One":[11],"problem":[12,139],"has":[14,66,121],"gained":[15],"visibility":[16],"over":[17],"the":[18,29,33,50,54,71,107,138,161],"past":[19],"years":[21],"of":[24,31,35,60,73,92,109,140,160],"Sentiment":[25],"Analysis.":[26],"This":[27],"process":[30],"determining":[32],"attitude":[34],"an":[36,102],"author":[37],"towards":[38],"some":[39,42],"subject":[40],"across":[41],"spectrum,":[43],"typically":[44],"\u201cpositive\u201d":[45],"or":[46,118],"\u201cnegative,\u201d":[47],"by":[48,158],"analyzing":[49],"textual":[51],"information.":[52],"Whereas":[53],"started":[56],"with":[57,62,70,94,101],"simple":[58,133],"counting":[59],"words":[61],"certain":[63],"characteristics,":[64],"it":[65],"grown":[67],"in":[68,164],"complexity":[69],"advent":[72],"deep":[74],"learning":[75],"and":[76,87,132,156,169],"neural":[77],"network":[78],"based":[79],"models.":[81],"Typically,":[82],"datasets":[83],"used":[84],"to":[85,112],"train":[86],"evaluate":[88],"these":[89],"models":[90,154],"consist":[91],"text":[93,120],"appropriate":[95],"labels,":[96],"such":[97,115],"as":[98,116],"movie":[99],"reviews":[100],"accompanied":[103],"star":[104],"rating.":[105],"However,":[106],"applicability":[108],"those":[110],"results":[111],"other":[113],"scenarios,":[114],"unstructured":[117],"natural":[119,147],"not":[122],"been":[123],"clear.":[124],"In":[125],"this":[126,165],"paper,":[127],"we":[128],"demonstrate":[129],"clear":[131],"case":[134],"shows":[136],"sentiment":[141],"analysis":[142],"fundamentally":[144],"unsuitable":[145],"for":[146],"text.":[148],"We":[149],"consider":[150],"state-of-the-art":[151],"black":[152],"box":[153],"developed":[155],"hosted":[157],"3":[159],"largest":[162],"companies":[163],"field:":[166],"Amazon,":[167],"Google":[168],"IBM.":[170]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}