{"id":"https://openalex.org/W2000877723","doi":"https://doi.org/10.1109/slt.2010.5700826","title":"Probabilistic model-based sentiment analysis of twitter messages","display_name":"Probabilistic model-based sentiment analysis of twitter messages","publication_year":2010,"publication_date":"2010-12-01","ids":{"openalex":"https://openalex.org/W2000877723","doi":"https://doi.org/10.1109/slt.2010.5700826","mag":"2000877723"},"language":"en","primary_location":{"id":"doi:10.1109/slt.2010.5700826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt.2010.5700826","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Spoken Language Technology Workshop","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/A5030468199","display_name":"Asl\u0131 \u00c7eliky\u0131lmaz","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Asli Celikyilmaz","raw_affiliation_strings":["University of California, Berkeley, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068709817","display_name":"Dilek Hakkani\u2010T\u00fcr","orcid":null},"institutions":[{"id":"https://openalex.org/I1297971548","display_name":"International Computer Science Institute","ror":"https://ror.org/01ewh7m12","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1297971548"]},{"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":["US"],"is_corresponding":false,"raw_author_name":"Dilek Hakkani-Tur","raw_affiliation_strings":["International Computer Science Institute, AT and T Research Laboratories, USA","Speech at Microsoft, Microsoft Research, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"International Computer Science Institute, AT and T Research Laboratories, USA","institution_ids":["https://openalex.org/I1297971548"]},{"raw_affiliation_string":"Speech at Microsoft, Microsoft Research, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079750750","display_name":"Junlan Feng","orcid":"https://orcid.org/0000-0001-5292-2945"},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junlan Feng","raw_affiliation_strings":["AT and T Research Laboratories, Florham Park, NJ, USA","AT&T Labs-Research, Florham Park, NJ"],"affiliations":[{"raw_affiliation_string":"AT and T Research Laboratories, Florham Park, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"AT&T Labs-Research, Florham Park, NJ","institution_ids":["https://openalex.org/I1283103587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030468199"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":7.2167,"has_fulltext":false,"cited_by_count":75,"citation_normalized_percentile":{"value":0.96884145,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"79","last_page":"84"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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":0.9998999834060669,"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":0.996999979019165,"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":0.9965000152587891,"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/sentiment-analysis","display_name":"Sentiment analysis","score":0.7599145770072937},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7500306367874146},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7101446390151978},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6407605409622192},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5280680656433105},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4823122024536133},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.47095590829849243},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32981613278388977}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7599145770072937},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7500306367874146},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7101446390151978},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6407605409622192},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5280680656433105},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4823122024536133},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.47095590829849243},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32981613278388977},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/slt.2010.5700826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt.2010.5700826","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Spoken Language Technology Workshop","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W40549020","https://openalex.org/W1880262756","https://openalex.org/W1998257453","https://openalex.org/W2022204871","https://openalex.org/W2053463056","https://openalex.org/W2059503205","https://openalex.org/W2063596712","https://openalex.org/W2106277949","https://openalex.org/W2124156373","https://openalex.org/W2133952599","https://openalex.org/W4231510805","https://openalex.org/W4255173720","https://openalex.org/W6601618085","https://openalex.org/W6639619044","https://openalex.org/W6678331010","https://openalex.org/W6680105712"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W1557905920","https://openalex.org/W2548633793","https://openalex.org/W2043093291"],"abstract_inverted_index":{"We":[0,13,60,78],"present":[1,61],"a":[2,81,103,124],"machine":[3],"learning":[4],"approach":[5,84],"to":[6,75],"sentiment":[7,28],"classification":[8,72,99,125],"on":[9,55,102],"twitter":[10],"messages":[11],"(tweets).":[12],"classify":[14],"each":[15],"tweet":[16],"into":[17],"two":[18],"categories:":[19],"polar":[20],"and":[21,49,58,70],"non-polar.":[22],"Tweets":[23],"with":[24,73,80,111],"positive":[25],"or":[26],"negative":[27],"are":[29,33,91,119],"considered":[30,34],"polar.":[31],"They":[32],"non-polar":[35],"otherwise.":[36],"Sentiment":[37],"analysis":[38],"of":[39,66,87,97,109],"tweets":[40,69],"can":[41],"potentially":[42],"benefit":[43],"different":[44,56],"parties,":[45],"such":[46],"as":[47,94],"consumers":[48],"marketing":[50],"researchers,":[51],"for":[52,63,85],"obtaining":[53],"opinions":[54],"products":[57],"services.":[59],"methods":[62],"text":[64],"normalization":[65],"the":[67,76,98,112],"noisy":[68],"their":[71],"respect":[74],"polarity.":[77],"experiment":[79],"mixture":[82],"model":[83],"generation":[86],"sentimental":[88],"words,":[89],"which":[90],"later":[92],"used":[93],"indicator":[95],"features":[96],"model.":[100],"Based":[101],"gold":[104],"standard":[105],"manually":[106],"annotated":[107],"ensemble":[108],"tweets,":[110],"new":[113],"approach,":[114],"we":[115],"obtain":[116],"F-scores":[117],"that":[118,127],"relatively":[120],"10%":[121],"better":[122],"than":[123],"baseline":[126],"uses":[128],"raw":[129],"word":[130],"n-gram":[131],"features.":[132]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":11},{"year":2012,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
