{"id":"https://openalex.org/W2436732713","doi":"https://doi.org/10.1109/icde.2016.7498225","title":"Topical influence modeling via topic-level interests and interactions on social curation services","display_name":"Topical influence modeling via topic-level interests and interactions on social curation services","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2436732713","doi":"https://doi.org/10.1109/icde.2016.7498225","mag":"2436732713"},"language":"en","primary_location":{"id":"doi:10.1109/icde.2016.7498225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2016.7498225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 32nd International Conference on Data Engineering (ICDE)","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/A5101885459","display_name":"Daehoon Kim","orcid":"https://orcid.org/0000-0003-0837-0877"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Daehoon Kim","raw_affiliation_strings":["Department of Knowledge Service Engineering, KAIST, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Knowledge Service Engineering, KAIST, Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112008082","display_name":"Jae-Gil Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae-Gil Lee","raw_affiliation_strings":["Department of Knowledge Service Engineering, KAIST, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Knowledge Service Engineering, KAIST, Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038390659","display_name":"Byung Suk Lee","orcid":"https://orcid.org/0000-0002-6019-5247"},"institutions":[{"id":"https://openalex.org/I111236770","display_name":"University of Vermont","ror":"https://ror.org/0155zta11","country_code":"US","type":"education","lineage":["https://openalex.org/I111236770"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Byung Suk Lee","raw_affiliation_strings":["Department of Computer Science, University of Vermont, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Vermont, U.S.A","institution_ids":["https://openalex.org/I111236770"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2082,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.90686101,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"3","issue":null,"first_page":"13","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.998199999332428,"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/T10028","display_name":"Topic Modeling","score":0.998199999332428,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":0.994700014591217,"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/computer-science","display_name":"Computer science","score":0.7832039594650269},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.713312029838562},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.6461242437362671},{"id":"https://openalex.org/keywords/data-curation","display_name":"Data curation","score":0.6335256099700928},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5472251772880554},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.5460973381996155},{"id":"https://openalex.org/keywords/spark","display_name":"SPARK (programming language)","score":0.5443413257598877},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5168336033821106},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.4928443431854248},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.4574747085571289},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4473181366920471},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.442261278629303},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.33291947841644287},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20886516571044922},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.11322838068008423}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7832039594650269},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.713312029838562},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.6461242437362671},{"id":"https://openalex.org/C91632574","wikidata":"https://www.wikidata.org/wiki/Q15088675","display_name":"Data curation","level":2,"score":0.6335256099700928},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5472251772880554},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.5460973381996155},{"id":"https://openalex.org/C2781215313","wikidata":"https://www.wikidata.org/wiki/Q3493345","display_name":"SPARK (programming language)","level":2,"score":0.5443413257598877},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5168336033821106},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.4928443431854248},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.4574747085571289},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4473181366920471},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.442261278629303},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33291947841644287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20886516571044922},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.11322838068008423},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icde.2016.7498225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2016.7498225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 32nd International Conference on Data Engineering (ICDE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W105935508","https://openalex.org/W1585529040","https://openalex.org/W1612003148","https://openalex.org/W1880262756","https://openalex.org/W1975583660","https://openalex.org/W1995343386","https://openalex.org/W2007954020","https://openalex.org/W2018984973","https://openalex.org/W2053105309","https://openalex.org/W2058616948","https://openalex.org/W2076219102","https://openalex.org/W2094736127","https://openalex.org/W2107559689","https://openalex.org/W2111551466","https://openalex.org/W2138167391","https://openalex.org/W2142517301","https://openalex.org/W2145677303","https://openalex.org/W2147880316","https://openalex.org/W2159973364","https://openalex.org/W2170344111","https://openalex.org/W2277141067","https://openalex.org/W2398784425","https://openalex.org/W2598224856","https://openalex.org/W4231510805","https://openalex.org/W4250589301","https://openalex.org/W4301480734","https://openalex.org/W6604317980","https://openalex.org/W6639619044","https://openalex.org/W6682082992","https://openalex.org/W6683277684","https://openalex.org/W6694856008","https://openalex.org/W6735469392"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W2093471820","https://openalex.org/W50079190","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W2111726165","https://openalex.org/W2347460059","https://openalex.org/W4308507533","https://openalex.org/W2407107767","https://openalex.org/W2901787049"],"abstract_inverted_index":{"Social":[0],"curation":[1,83,91],"services":[2],"are":[3],"emerging":[4],"social":[5,57,82,90],"media":[6],"platforms":[7],"that":[8,143],"enable":[9],"users":[10,38,88],"to":[11,16,60,85,119,150],"curate":[12],"their":[13,21],"contents":[14,34,114],"according":[15],"the":[17,24,37,55,63,78,97,106,162],"topic":[18,25],"and":[19,115,138,153,174],"express":[20],"interests":[22],"at":[23],"level":[26],"by":[27,96,148],"following":[28],"curated":[29],"collections":[30],"of":[31,65,105,182],"other":[32,163],"users'":[33],"rather":[35],"than":[36,161],"themselves.":[39],"The":[40,140],"topic-level":[41,109],"information":[42,110],"revealed":[43],"through":[44],"this":[45,70],"new":[46],"feature":[47],"far":[48],"exceeds":[49],"what":[50],"existing":[51],"methods":[52],"solicit":[53],"from":[54,89,136],"traditional":[56],"networking":[58],"services,":[59],"greatly":[61],"enhance":[62],"quality":[64],"topic-sensitive":[66],"influence":[67,80],"modeling.":[68],"In":[69,117],"paper,":[71],"we":[72,123,166],"propose":[73],"a":[74,168,180],"novel":[75],"model":[76],"called":[77],"topical":[79],"with":[81,127],"(TISC)":[84],"find":[86],"influential":[87],"services.":[92],"This":[93],"model,":[94],"formulated":[95],"continuous":[98],"conditional":[99],"random":[100],"field,":[101],"fully":[102],"takes":[103],"advantage":[104],"explicitly":[107],"available":[108],"reflected":[111],"in":[112,158],"both":[113],"interactions.":[116],"order":[118],"validate":[120],"its":[121,176],"merits,":[122],"comprehensively":[124],"compare":[125],"TISC":[126,144],"state-of-the-art":[128],"models":[129],"using":[130],"two":[131],"real-world":[132],"data":[133],"sets":[134],"collected":[135],"Pinterest":[137],"Scoop.it.":[139],"results":[141,157],"show":[142],"achieves":[145],"higher":[146],"accuracy":[147],"up":[149],"around":[151],"80%":[152],"finds":[154],"more":[155],"convincing":[156],"case":[159],"studies":[160],"models.":[164],"Moreover,":[165],"develop":[167],"distributed":[169],"learning":[170],"algorithm":[171],"on":[172,179],"Spark":[173],"demonstrate":[175],"excellent":[177],"scalability":[178],"cluster":[181],"48":[183],"cores.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
