{"id":"https://openalex.org/W4291713061","doi":"https://doi.org/10.1145/2661829.2662005","title":"Twitter Opinion Topic Model","display_name":"Twitter Opinion Topic Model","publication_year":2014,"publication_date":"2014-11-03","ids":{"openalex":"https://openalex.org/W4291713061","doi":"https://doi.org/10.1145/2661829.2662005"},"language":"en","primary_location":{"id":"doi:10.1145/2661829.2662005","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2661829.2662005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"preprint","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/A5041793725","display_name":"Kar Wai Lim","orcid":"https://orcid.org/0000-0003-0979-1956"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Kar Wai Lim","raw_affiliation_strings":["Australian National University, Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"Australian National University, Canberra, Australia","institution_ids":["https://openalex.org/I118347636"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005792924","display_name":"Wray Buntine","orcid":"https://orcid.org/0000-0001-9292-1015"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wray Buntine","raw_affiliation_strings":["Monash University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Monash University, Melbourne, Australia","institution_ids":["https://openalex.org/I56590836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041793725"],"corresponding_institution_ids":["https://openalex.org/I118347636"],"apc_list":null,"apc_paid":null,"fwci":8.21067788,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.97195879,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1319","last_page":"1328"},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9976000189781189,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9258854389190674},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.7713185548782349},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7441097497940063},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.6190273761749268},{"id":"https://openalex.org/keywords/public-opinion","display_name":"Public opinion","score":0.6051055788993835},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.6035058498382568},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5702387690544128},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5581223964691162},{"id":"https://openalex.org/keywords/microblogging","display_name":"Microblogging","score":0.4809359908103943},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.46447670459747314},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.4606779217720032},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4243842661380768},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36740922927856445},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3590414524078369},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.19365975260734558},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.09572175145149231}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.9258854389190674},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.7713185548782349},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7441097497940063},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.6190273761749268},{"id":"https://openalex.org/C134698397","wikidata":"https://www.wikidata.org/wiki/Q17946","display_name":"Public opinion","level":3,"score":0.6051055788993835},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.6035058498382568},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5702387690544128},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5581223964691162},{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.4809359908103943},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.46447670459747314},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.4606779217720032},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4243842661380768},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36740922927856445},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3590414524078369},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.19365975260734558},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.09572175145149231},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2661829.2662005","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2661829.2662005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W32980360","https://openalex.org/W40549020","https://openalex.org/W157541337","https://openalex.org/W166614460","https://openalex.org/W193524605","https://openalex.org/W203054622","https://openalex.org/W371426616","https://openalex.org/W1506246224","https://openalex.org/W1508977358","https://openalex.org/W1581485226","https://openalex.org/W1850562331","https://openalex.org/W1859957297","https://openalex.org/W1907257599","https://openalex.org/W1924133215","https://openalex.org/W1964613733","https://openalex.org/W1967274749","https://openalex.org/W2001587475","https://openalex.org/W2004192095","https://openalex.org/W2005902041","https://openalex.org/W2016443085","https://openalex.org/W2022204871","https://openalex.org/W2023276992","https://openalex.org/W2028904519","https://openalex.org/W2044429219","https://openalex.org/W2047676437","https://openalex.org/W2084046180","https://openalex.org/W2087045154","https://openalex.org/W2096110600","https://openalex.org/W2099653665","https://openalex.org/W2108420397","https://openalex.org/W2112056172","https://openalex.org/W2112251034","https://openalex.org/W2113125055","https://openalex.org/W2129294185","https://openalex.org/W2129604374","https://openalex.org/W2153848201","https://openalex.org/W2154099718","https://openalex.org/W2154970197","https://openalex.org/W2161228561","https://openalex.org/W2168332560","https://openalex.org/W2169200297","https://openalex.org/W2250243742","https://openalex.org/W4205184193","https://openalex.org/W4239946314","https://openalex.org/W4248506559","https://openalex.org/W4298252756","https://openalex.org/W4313490656","https://openalex.org/W6718766952","https://openalex.org/W6805520290"],"related_works":["https://openalex.org/W2769501189","https://openalex.org/W4315588616","https://openalex.org/W4312773271","https://openalex.org/W2494246486","https://openalex.org/W2888805565","https://openalex.org/W2962686197","https://openalex.org/W2346975490","https://openalex.org/W2888662092","https://openalex.org/W1540611520","https://openalex.org/W2122605835"],"abstract_inverted_index":{"Aspect-based":[0],"opinion":[1,51,76,85,94,119,131,199],"mining":[2,95],"is":[3,21,160],"widely":[4],"applied":[5],"to":[6,9],"review":[7,55],"data":[8,32,65],"aggregate":[10],"or":[11],"summarize":[12],"opinions":[13,208],"of":[14,143,186,204],"a":[15,140,149],"product,":[16],"and":[17,62,69,96,104,166,181,192],"the":[18,123,169,183],"current":[19],"state-of-the-art":[20],"achieved":[22],"with":[23,37,168],"Latent":[24],"Dirichlet":[25],"Allocation":[26],"(LDA)-based":[27],"model.":[28],"Although":[29],"social":[30],"media":[31],"like":[33],"tweets":[34,112,177,205],"are":[35,58,109],"laden":[36],"opinions,":[38],"their":[39],"\"dirty\"":[40],"nature":[41],"(as":[42],"natural":[43],"language)":[44],"has":[45],"discouraged":[46],"researchers":[47],"from":[48],"applying":[49],"LDA-based":[50,84],"model":[52,86],"for":[53,74,93],"product":[54,75],"mining.":[56,77],"Tweets":[57],"often":[59],"informal,":[60],"unstructured":[61],"lacking":[63],"labeled":[64],"such":[66],"as":[67],"categories":[68],"ratings,":[70],"making":[71],"it":[72,164],"challenging":[73],"In":[78],"this":[79],"paper,":[80],"we":[81,138],"propose":[82,139],"an":[83,154],"named":[87],"Twitter":[88],"Opinion":[89],"Topic":[90],"Model":[91],"(TOTM)":[92],"sentiment":[97,106,145,157],"analysis.":[98,194],"TOTM":[99,187],"leverages":[100],"hashtags,":[101],"mentions,":[102],"emoticons":[103],"strong":[105],"words":[107],"that":[108,163,197],"present":[110],"in":[111,113,134,162,188],"its":[114],"discovery":[115],"process.":[116],"It":[117],"improves":[118],"prediction":[120],"by":[121,152],"modeling":[122],"target-opinion":[124],"interaction":[125],"directly,":[126],"thus":[127],"discovering":[128],"target":[129],"specific":[130],"words,":[132],"neglected":[133],"existing":[135,155],"approaches.":[136],"Moreover,":[137],"new":[141],"formulation":[142],"incorporating":[144],"prior":[146],"information":[147],"into":[148],"topic":[150],"model,":[151],"utilizing":[153],"public":[156],"lexicon.":[158],"This":[159],"novel":[161],"learns":[165],"updates":[167],"data.":[170],"We":[171,195],"conduct":[172],"experiments":[173],"on":[174,178,201,209],"9":[175],"million":[176],"electronic":[179],"products,":[180],"demonstrate":[182],"improved":[184],"performance":[185],"both":[189],"quantitative":[190],"evaluations":[191],"qualitative":[193],"show":[196],"aspect-based":[198],"analysis":[200],"massive":[202],"volume":[203],"provides":[206],"useful":[207],"products.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":3}],"updated_date":"2026-02-12T00:53:03.260389","created_date":"2022-08-16T00:00:00"}
