{"id":"https://openalex.org/W3205762456","doi":"https://doi.org/10.1109/idaacs53288.2021.9660838","title":"Construction and Performance Analysis of a Groomed Polarity Lexicon Derived from Product Review Source Datasets","display_name":"Construction and Performance Analysis of a Groomed Polarity Lexicon Derived from Product Review Source Datasets","publication_year":2021,"publication_date":"2021-09-22","ids":{"openalex":"https://openalex.org/W3205762456","doi":"https://doi.org/10.1109/idaacs53288.2021.9660838","mag":"3205762456"},"language":"en","primary_location":{"id":"doi:10.1109/idaacs53288.2021.9660838","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idaacs53288.2021.9660838","pdf_url":null,"source":{"id":"https://openalex.org/S4363607971","display_name":"2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","raw_type":"proceedings-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/A5014563986","display_name":"D.C. Colley","orcid":"https://orcid.org/0000-0002-0092-6837"},"institutions":[{"id":"https://openalex.org/I198012923","display_name":"University of Staffordshire","ror":"https://ror.org/00d6k8y35","country_code":"GB","type":"education","lineage":["https://openalex.org/I198012923"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Derek Colley","raw_affiliation_strings":["School of Digital, Technologies and Arts, Staffordshire University, Stoke-on-Trent, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Digital, Technologies and Arts, Staffordshire University, Stoke-on-Trent, United Kingdom","institution_ids":["https://openalex.org/I198012923"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044130288","display_name":"Asaduzzaman Asaduzzaman","orcid":"https://orcid.org/0000-0001-5418-2450"},"institutions":[{"id":"https://openalex.org/I198012923","display_name":"University of Staffordshire","ror":"https://ror.org/00d6k8y35","country_code":"GB","type":"education","lineage":["https://openalex.org/I198012923"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Md Asaduzzaman","raw_affiliation_strings":["School of Digital, Technologies and Arts, Staffordshire University, Stoke-on-Trent, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Digital, Technologies and Arts, Staffordshire University, Stoke-on-Trent, United Kingdom","institution_ids":["https://openalex.org/I198012923"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10609982,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"875","last_page":"880"},"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":0.9876000285148621,"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":0.9868999719619751,"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/lexicon","display_name":"Lexicon","score":0.724466860294342},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7217317223548889},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5914764404296875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5598726868629456},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5184309482574463},{"id":"https://openalex.org/keywords/judgement","display_name":"Judgement","score":0.5182609558105469},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.49196740984916687},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4851849675178528},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4740833044052124},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4554937779903412},{"id":"https://openalex.org/keywords/f1-score","display_name":"F1 score","score":0.43540000915527344},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4265541434288025},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30593788623809814},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1300775408744812}],"concepts":[{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.724466860294342},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7217317223548889},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5914764404296875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5598726868629456},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5184309482574463},{"id":"https://openalex.org/C2776548248","wikidata":"https://www.wikidata.org/wiki/Q12621536","display_name":"Judgement","level":2,"score":0.5182609558105469},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.49196740984916687},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4851849675178528},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4740833044052124},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4554937779903412},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.43540000915527344},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4265541434288025},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30593788623809814},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1300775408744812},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/idaacs53288.2021.9660838","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idaacs53288.2021.9660838","pdf_url":null,"source":{"id":"https://openalex.org/S4363607971","display_name":"2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.staffs.ac.uk:7029","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401113","display_name":"Staffordshire Online Repository (Staffordshire University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I198012923","host_organization_name":"University of Staffordshire","host_organization_lineage":["https://openalex.org/I198012923"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Book Chapter, Section or Conference Proceeding"},{"id":"mag:3205762456","is_oa":false,"landing_page_url":"http://eprints.staffs.ac.uk/7029/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2028140375","https://openalex.org/W2078630890","https://openalex.org/W2084046180","https://openalex.org/W2401379394","https://openalex.org/W2541280461","https://openalex.org/W2598013184","https://openalex.org/W2606063593","https://openalex.org/W2606675507","https://openalex.org/W2780698117","https://openalex.org/W2793625747","https://openalex.org/W2810374907","https://openalex.org/W2910636646","https://openalex.org/W2971196067","https://openalex.org/W4240008398","https://openalex.org/W6676621845"],"related_works":["https://openalex.org/W2807005386","https://openalex.org/W2907910042","https://openalex.org/W2103427667","https://openalex.org/W1659908699","https://openalex.org/W2584660656","https://openalex.org/W3013306728","https://openalex.org/W3155430395","https://openalex.org/W2982163590","https://openalex.org/W2951563156","https://openalex.org/W2750661478","https://openalex.org/W2468530725","https://openalex.org/W2877316863","https://openalex.org/W2295077356","https://openalex.org/W148415288","https://openalex.org/W2250765489","https://openalex.org/W3006998941","https://openalex.org/W2163885650","https://openalex.org/W2075118955","https://openalex.org/W2991227596","https://openalex.org/W2112162967"],"abstract_inverted_index":{"Using":[0],"a":[1,38,49,68,108,167,184],"large,":[2],"publicly-available":[3],"dataset":[4,47,70,102,112],"[1],":[5],"we":[6,89,106,174],"extract":[7],"over":[8],"51":[9],"million":[10],"product":[11],"reviews.":[12],"We":[13,41,124,144,190],"split":[14],"and":[15,27,34,53,91,117,197,200],"associate":[16],"each":[17,20,73],"word":[18,60],"of":[19,71,100,158,203],"review":[21,25,64],"comment":[22],"with":[23,75,161],"the":[24,29,43,46,94,98,101,140,171,201,204],"score":[26,35,83],"store":[28],"resulting":[30],"3.7":[31],"billion":[32],"word-":[33],"pairs":[36],"in":[37,156,207],"relational":[39],"database.":[40],"cleanse":[42],"data,":[44],"grooming":[45],"against":[48,121,130],"standard":[50],"English":[51],"dictionary,":[52],"create":[54],"an":[55,76],"aggregation":[56],"model":[57,69,128,147,177],"based":[58,84],"on":[59,85],"count":[61],"distributions":[62],"across":[63,93],"scores.":[65],"This":[66],"renders":[67],"words,":[72],"associated":[74],"overall":[77],"positive":[78],"or":[79],"negative":[80],"polarity":[81],"sentiment":[82,104,119],"star":[86],"rating":[87],"which":[88],"correct":[90,154],"normalise":[92],"set.":[95],"To":[96],"test":[97],"efficacy":[99],"for":[103,187],"classification,":[105],"ingest":[107],"secondary":[109],"cross-domain":[110],"public":[111],"containing":[113],"freeform":[114],"text":[115],"data":[116,142,210],"perform":[118],"analysis":[120],"this":[122],"dataset.":[123],"then":[125],"compare":[126],"our":[127,146,176,195],"performance":[129,133],"human":[131,136,149,180],"classification":[132],"by":[134],"enlisting":[135],"volunteers":[137],"to":[138,182,194],"rate":[139],"same":[141],"samples.":[143],"find":[145,175],"emulates":[148],"judgement":[150,181],"reasonably":[151],"well,":[152],"reaching":[153],"conclusions":[155],"56%":[157],"cases,":[159],"albeit":[160],"significant":[162],"variance":[163],"when":[164],"classifying":[165],"at":[166],"coarse":[168],"grain.":[169],"At":[170],"fine":[172],"grain,":[173],"can":[178],"track":[179],"within":[183],"7%":[185],"margin":[186],"some":[188],"cases.":[189],"consider":[191],"potential":[192],"improvements":[193],"method":[196],"further":[198],"applications,":[199],"limitations":[202],"lexicon-based":[205],"approach":[206],"cross-domain,":[208],"big":[209],"environments.":[211]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
