{"id":"https://openalex.org/W2006150671","doi":"https://doi.org/10.1145/1514888.1514893","title":"Modeling information-seeker satisfaction in community question answering","display_name":"Modeling information-seeker satisfaction in community question answering","publication_year":2009,"publication_date":"2009-04-01","ids":{"openalex":"https://openalex.org/W2006150671","doi":"https://doi.org/10.1145/1514888.1514893","mag":"2006150671"},"language":"en","primary_location":{"id":"doi:10.1145/1514888.1514893","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1514888.1514893","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-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/A5028578280","display_name":"Eugene Agichtein","orcid":"https://orcid.org/0000-0002-3148-5448"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eugene Agichtein","raw_affiliation_strings":["Emory University, Atlanta, GA","Emory university, Atlanta, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Emory University, Atlanta, GA","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Emory university, Atlanta, GA","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022201710","display_name":"Yandong Liu","orcid":"https://orcid.org/0000-0002-0755-2014"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yandong Liu","raw_affiliation_strings":["Emory University, Atlanta, GA","Emory university, Atlanta, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Emory University, Atlanta, GA","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Emory university, Atlanta, GA","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021438219","display_name":"Jiang Bian","orcid":"https://orcid.org/0000-0001-6997-1989"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiang Bian","raw_affiliation_strings":["Gerogia Institute of Technology, Atlanta, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gerogia Institute of Technology, Atlanta, GA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":13.8855,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.98580642,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"3","issue":"2","first_page":"1","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":1.0,"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"}},{"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/question-answering","display_name":"Question answering","score":0.775131106376648},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.731118381023407},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.6695132255554199},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5654276013374329},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5457727909088135},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.543393611907959},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.5288045406341553},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.490325003862381},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.453596293926239},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3428894877433777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2092646062374115}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.775131106376648},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.731118381023407},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6695132255554199},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5654276013374329},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5457727909088135},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.543393611907959},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.5288045406341553},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.490325003862381},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.453596293926239},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3428894877433777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2092646062374115},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1514888.1514893","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1514888.1514893","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W35400180","https://openalex.org/W198220271","https://openalex.org/W348133106","https://openalex.org/W593909917","https://openalex.org/W1508509952","https://openalex.org/W1512098439","https://openalex.org/W1542825220","https://openalex.org/W1554394657","https://openalex.org/W1570448133","https://openalex.org/W1833977909","https://openalex.org/W1973697738","https://openalex.org/W1974360117","https://openalex.org/W2001575924","https://openalex.org/W2003150093","https://openalex.org/W2037250113","https://openalex.org/W2037858832","https://openalex.org/W2046325278","https://openalex.org/W2050914789","https://openalex.org/W2075893676","https://openalex.org/W2098479684","https://openalex.org/W2099391294","https://openalex.org/W2102956348","https://openalex.org/W2104217798","https://openalex.org/W2112076978","https://openalex.org/W2115758952","https://openalex.org/W2120196261","https://openalex.org/W2130937896","https://openalex.org/W2134568263","https://openalex.org/W2149156280","https://openalex.org/W2158450083","https://openalex.org/W2161152375","https://openalex.org/W2162355876","https://openalex.org/W2560674852","https://openalex.org/W2593172760","https://openalex.org/W2598654328","https://openalex.org/W2608239929","https://openalex.org/W2741609678","https://openalex.org/W2966207845"],"related_works":["https://openalex.org/W2384605597","https://openalex.org/W2387743295","https://openalex.org/W2115758952","https://openalex.org/W2109940557","https://openalex.org/W3082787378","https://openalex.org/W2136007095","https://openalex.org/W2466832359","https://openalex.org/W2366230879","https://openalex.org/W3208425359","https://openalex.org/W2349927912"],"abstract_inverted_index":{"Question":[0],"Answering":[1],"Communities":[2],"such":[3,235],"as":[4,13,236],"Naver,":[5],"Baidu":[6],"Knows,":[7],"and":[8,15,52,80,134,141,160,168,183,205,225,244,247],"Yahoo!":[9],"Answers":[10],"have":[11,46],"emerged":[12],"popular,":[14],"often":[16],"effective,":[17],"means":[18],"of":[19,43,50,55,57,98,138,157,166,180,202,233],"information":[20,33,100,184,194],"seeking":[21,185],"on":[22],"the":[23,96,121,125,164,181],"web.":[24],"By":[25],"posting":[26],"questions":[27,159],"for":[28,144,230],"other":[29,60],"participants":[30],"to":[31,39,111],"answer,":[32],"seekers":[34],"can":[35,214],"obtain":[36,74],"specific":[37],"answers":[38,58,122],"their":[40],"questions.":[41],"Users":[42],"CQA":[44,63],"portals":[45],"already":[47],"contributed":[48],"millions":[49,56],"questions,":[51],"received":[53],"hundreds":[54],"from":[59,151],"participants.":[61,127],"However,":[62],"is":[64,92],"not":[65],"always":[66],"effective:":[67],"in":[68,81,103,187],"some":[69],"cases,":[70],"a":[71,75,89,114,130,136,152,177,220,231],"user":[72,161,237],"may":[73,84],"perfect":[76],"answer":[77,91,240],"within":[78],"minutes,":[79],"others":[82],"it":[83],"require":[85],"hours\u2014and":[86],"sometimes":[87],"days\u2014until":[88],"satisfactory":[90],"contributed.":[93],"We":[94,128,172,197],"investigate":[95],"problem":[97],"predicting":[99,169],"seeker":[101,195],"satisfaction":[102],"collaborative":[104],"question":[105,115,188],"answering":[106,189],"communities,":[107],"where":[108],"we":[109],"attempt":[110],"predict":[112],"whether":[113],"author":[116],"will":[117],"be":[118,228],"satisfied":[119],"with":[120,176,193],"submitted":[123],"by":[124],"community":[126],"present":[129],"general":[131],"prediction":[132,217],"model,":[133],"develop":[135],"variety":[137,232],"content,":[139],"structure,":[140],"community-focused":[142],"features":[143],"this":[145],"task.":[146],"Our":[147,223],"experimental":[148],"results,":[149],"obtained":[150],"large-scale":[153],"evaluation":[154],"over":[155,219],"thousands":[156],"real":[158],"ratings,":[162],"demonstrate":[163],"feasibility":[165],"modeling":[167],"asker":[170,203],"satisfaction.":[171,196],"complement":[173],"our":[174],"results":[175],"thorough":[178],"investigation":[179],"interactions":[182],"patterns":[186],"communities":[190],"that":[191,207],"correlate":[192],"also":[198],"explore":[199],"personalized":[200],"models":[201,224],"satisfaction,":[204],"show":[206],"when":[208],"sufficient":[209],"interaction":[210],"history":[211],"exists,":[212],"personalization":[213],"significantly":[215],"improve":[216],"accuracy":[218],"\u201cone-size-fits-all\u201d":[221],"model.":[222],"predictions":[226],"could":[227],"useful":[229],"applications,":[234],"intent":[238],"inference,":[239],"ranking,":[241],"interface":[242],"design,":[243],"query":[245],"suggestion":[246],"routing.":[248]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":7}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
