{"id":"https://openalex.org/W2119408773","doi":"https://doi.org/10.1162/coli_a_00221","title":"A Statistical Parsing Framework for Sentiment Classification","display_name":"A Statistical Parsing Framework for Sentiment Classification","publication_year":2015,"publication_date":"2015-04-30","ids":{"openalex":"https://openalex.org/W2119408773","doi":"https://doi.org/10.1162/coli_a_00221","mag":"2119408773"},"language":"en","primary_location":{"id":"doi:10.1162/coli_a_00221","is_oa":true,"landing_page_url":"https://doi.org/10.1162/coli_a_00221","pdf_url":"https://www.mitpressjournals.org/doi/pdf/10.1162/COLI_a_00221","source":{"id":"https://openalex.org/S155526855","display_name":"Computational Linguistics","issn_l":"0891-2017","issn":["0891-2017","1530-9312"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Linguistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.mitpressjournals.org/doi/pdf/10.1162/COLI_a_00221","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103661051","display_name":"Li Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Dong","raw_affiliation_strings":["Beihang University","Beihang Univ.#TAB#"],"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Beihang Univ.#TAB#","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014662947","display_name":"Furu Wei","orcid":"https://orcid.org/0000-0002-7810-5852"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Furu Wei","raw_affiliation_strings":["Microsoft Research","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101635405","display_name":"Shujie Liu","orcid":"https://orcid.org/0009-0008-0785-8882"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Shujie Liu","raw_affiliation_strings":["Microsoft Research","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701572","display_name":"Ming Zhou","orcid":"https://orcid.org/0000-0002-2551-2964"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Ming Zhou","raw_affiliation_strings":["Microsoft Research","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107234003","display_name":"Ke Xu","orcid":"https://orcid.org/0000-0001-5447-8008"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Xu","raw_affiliation_strings":["Beihang University","Beihang Univ.#TAB#"],"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Beihang Univ.#TAB#","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103661051"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":12.9077,"has_fulltext":true,"cited_by_count":61,"citation_normalized_percentile":{"value":0.98645739,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"41","issue":"2","first_page":"293","last_page":"336"},"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/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9990000128746033,"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":0.8862124085426331},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7883390188217163},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.7699751853942871},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7446227669715881},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7195759415626526},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.6364742517471313},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6310631036758423},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5299497842788696},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.47213393449783325},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4160473942756653}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8862124085426331},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7883390188217163},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7699751853942871},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7446227669715881},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7195759415626526},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.6364742517471313},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6310631036758423},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5299497842788696},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.47213393449783325},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4160473942756653},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C1491633281","wikidata":"https://www.wikidata.org/wiki/Q7868","display_name":"Cell","level":2,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1162/coli_a_00221","is_oa":true,"landing_page_url":"https://doi.org/10.1162/coli_a_00221","pdf_url":"https://www.mitpressjournals.org/doi/pdf/10.1162/COLI_a_00221","source":{"id":"https://openalex.org/S155526855","display_name":"Computational Linguistics","issn_l":"0891-2017","issn":["0891-2017","1530-9312"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Linguistics","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.755.175","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.755.175","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1401.6330.pdf","raw_type":"text"},{"id":"pmh:oai:doaj.org/article:0a9de46a73fa42a6b742f777ada380a8","is_oa":true,"landing_page_url":"https://doaj.org/article/0a9de46a73fa42a6b742f777ada380a8","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computational Linguistics, Vol 41, Iss 2 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1162/coli_a_00221","is_oa":true,"landing_page_url":"https://doi.org/10.1162/coli_a_00221","pdf_url":"https://www.mitpressjournals.org/doi/pdf/10.1162/COLI_a_00221","source":{"id":"https://openalex.org/S155526855","display_name":"Computational Linguistics","issn_l":"0891-2017","issn":["0891-2017","1530-9312"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Linguistics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G3935756157","display_name":null,"funder_award_id":"142100","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8055127673","display_name":null,"funder_award_id":"61421003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326978","display_name":"State Key Laboratory of Software Development Environment","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2119408773.pdf","grobid_xml":"https://content.openalex.org/works/W2119408773.grobid-xml"},"referenced_works_count":90,"referenced_works":["https://openalex.org/W71795751","https://openalex.org/W104703790","https://openalex.org/W147290778","https://openalex.org/W233613663","https://openalex.org/W1502293651","https://openalex.org/W1506285740","https://openalex.org/W1532325895","https://openalex.org/W1540934181","https://openalex.org/W1559723967","https://openalex.org/W1567570606","https://openalex.org/W1582344906","https://openalex.org/W1598251544","https://openalex.org/W1631260214","https://openalex.org/W1632114991","https://openalex.org/W1743243001","https://openalex.org/W1889268436","https://openalex.org/W1951269370","https://openalex.org/W1970961429","https://openalex.org/W1972846540","https://openalex.org/W1992039201","https://openalex.org/W1994616650","https://openalex.org/W2013994393","https://openalex.org/W2014902591","https://openalex.org/W2062837929","https://openalex.org/W2063596712","https://openalex.org/W2077587655","https://openalex.org/W2080558111","https://openalex.org/W2082092506","https://openalex.org/W2084046180","https://openalex.org/W2086277751","https://openalex.org/W2096631398","https://openalex.org/W2097162496","https://openalex.org/W2097606805","https://openalex.org/W2097726431","https://openalex.org/W2098018055","https://openalex.org/W2108646579","https://openalex.org/W2111742432","https://openalex.org/W2112251034","https://openalex.org/W2113459411","https://openalex.org/W2114524997","https://openalex.org/W2115176538","https://openalex.org/W2116410915","https://openalex.org/W2118585731","https://openalex.org/W2120340025","https://openalex.org/W2121276225","https://openalex.org/W2124022436","https://openalex.org/W2124479173","https://openalex.org/W2125712079","https://openalex.org/W2131090205","https://openalex.org/W2131305515","https://openalex.org/W2132166724","https://openalex.org/W2136680862","https://openalex.org/W2138260386","https://openalex.org/W2139686600","https://openalex.org/W2140266767","https://openalex.org/W2141790691","https://openalex.org/W2142898321","https://openalex.org/W2146111747","https://openalex.org/W2146338426","https://openalex.org/W2146502635","https://openalex.org/W2152096446","https://openalex.org/W2152907450","https://openalex.org/W2154359981","https://openalex.org/W2154416898","https://openalex.org/W2155227495","https://openalex.org/W2155328222","https://openalex.org/W2156953626","https://openalex.org/W2160052288","https://openalex.org/W2161002933","https://openalex.org/W2162860143","https://openalex.org/W2163274265","https://openalex.org/W2163455955","https://openalex.org/W2166706824","https://openalex.org/W2167665328","https://openalex.org/W2172678396","https://openalex.org/W2189089430","https://openalex.org/W2190850524","https://openalex.org/W2199803028","https://openalex.org/W2234490075","https://openalex.org/W2250562110","https://openalex.org/W2251062127","https://openalex.org/W2251939518","https://openalex.org/W2262894244","https://openalex.org/W2437005631","https://openalex.org/W2787893582","https://openalex.org/W2911246871","https://openalex.org/W2914096745","https://openalex.org/W3146306708","https://openalex.org/W4205184193","https://openalex.org/W4210956481"],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W2941935829","https://openalex.org/W3089396779","https://openalex.org/W2354902965","https://openalex.org/W2596247554","https://openalex.org/W4301373556","https://openalex.org/W3013279174","https://openalex.org/W3132372214","https://openalex.org/W2400337198","https://openalex.org/W1984947604"],"abstract_inverted_index":{"We":[0,38,69,88,128],"present":[1],"a":[2,26,36,64,80,100,166,171],"statistical":[3,27],"parsing":[4,19,86,91],"framework":[5],"for":[6,21,99],"sentence-level":[7],"sentiment":[8,22,33,44,61,72,85,96,112,126,140,167,182,197],"classification":[9,198],"in":[10,43,63],"this":[11],"article.":[12],"Unlike":[13],"previous":[14],"works":[15],"that":[16,40],"use":[17],"syntactic":[18,146],"results":[20],"analysis,":[23],"we":[24,156,164],"develop":[25,89],"parser":[28,131],"to":[29,93,109,122],"directly":[30,132],"analyze":[31],"the":[32,54,71,84,90,104,111,117,124,130],"structure":[34],"of":[35,83,135,151,174],"sentence.":[37],"show":[39,192],"complicated":[41],"phenomena":[42],"analysis":[45],"(e.g.,":[46],"negation,":[47],"intensification,":[48],"and":[49,59,66,78,114,116],"contrast)":[50],"can":[51,157],"be":[52],"handled":[53],"same":[55],"way":[56],"as":[57,180],"simple":[58],"straightforward":[60],"expressions":[62],"unified":[65],"probabilistic":[67],"way.":[68],"formulate":[70],"grammar":[73],"upon":[74],"Context-Free":[75],"Grammars":[76],"(CFGs),":[77],"provide":[79],"formal":[81],"description":[82],"framework.":[87],"model":[92,106,119],"obtain":[94,158],"possible":[95],"parse":[97],"trees":[98],"sentence,":[101],"from":[102,133,170],"which":[103],"polarity":[105,141,149,183],"is":[107,120],"proposed":[108],"derive":[110],"strength":[113],"polarity,":[115],"ranking":[118],"dedicated":[121],"selecting":[123],"best":[125],"tree.":[127],"train":[129,165],"examples":[134],"sentences":[136,176],"annotated":[137],"only":[138],"with":[139,177],"labels":[142],"but":[143],"without":[144],"any":[145],"annotations":[147,150],"or":[148],"constituents":[152],"within":[153],"sentences.":[154],"Therefore":[155],"training":[159],"data":[160,190],"easily.":[161],"In":[162],"particular,":[163],"parser,":[168],"s.parser,":[169],"large":[172],"amount":[173],"review":[175],"users'":[178],"ratings":[179],"rough":[181],"labels.":[184],"Extensive":[185],"experiments":[186],"on":[187],"existing":[188],"benchmark":[189],"sets":[191],"significant":[193],"improvements":[194],"over":[195],"baseline":[196],"approaches.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
