{"id":"https://openalex.org/W2510927418","doi":"https://doi.org/10.1145/2959100.2959147","title":"Mood-Sensitive Truth Discovery For Reliable Recommendation Systems in Social Sensing","display_name":"Mood-Sensitive Truth Discovery For Reliable Recommendation Systems in Social Sensing","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2510927418","doi":"https://doi.org/10.1145/2959100.2959147","mag":"2510927418"},"language":"en","primary_location":{"id":"doi:10.1145/2959100.2959147","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2959100.2959147","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM Conference on Recommender Systems","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/A5087354670","display_name":"Jermaine Marshall","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jermaine Marshall","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100391517","display_name":"Dong Wang","orcid":"https://orcid.org/0000-0002-9599-8023"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dong Wang","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087354670"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":16.0258,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.98620535,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"167","last_page":"174"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":1.0,"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"}},{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9965000152587891,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/credibility","display_name":"Credibility","score":0.8034824132919312},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.7748360633850098},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6901121735572815},{"id":"https://openalex.org/keywords/mood","display_name":"Mood","score":0.646835446357727},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5835118293762207},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.544059157371521},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5352429151535034},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39884746074676514},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.332591712474823},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.24043676257133484},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.18341341614723206},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.14115196466445923},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.11038810014724731},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.0865897536277771}],"concepts":[{"id":"https://openalex.org/C2780224610","wikidata":"https://www.wikidata.org/wiki/Q1530061","display_name":"Credibility","level":2,"score":0.8034824132919312},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.7748360633850098},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6901121735572815},{"id":"https://openalex.org/C2780733359","wikidata":"https://www.wikidata.org/wiki/Q331769","display_name":"Mood","level":2,"score":0.646835446357727},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5835118293762207},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.544059157371521},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5352429151535034},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39884746074676514},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.332591712474823},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.24043676257133484},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.18341341614723206},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14115196466445923},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.11038810014724731},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0865897536277771},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2959100.2959147","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2959100.2959147","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G3313389185","display_name":null,"funder_award_id":"69595-CS-II","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1491825830","https://openalex.org/W1497702967","https://openalex.org/W1571497207","https://openalex.org/W1597703625","https://openalex.org/W1967647772","https://openalex.org/W1971494700","https://openalex.org/W1975132007","https://openalex.org/W1979698145","https://openalex.org/W1998212475","https://openalex.org/W2012638909","https://openalex.org/W2052880471","https://openalex.org/W2094634352","https://openalex.org/W2103112159","https://openalex.org/W2108365287","https://openalex.org/W2118388899","https://openalex.org/W2125635328","https://openalex.org/W2127977814","https://openalex.org/W2135790056","https://openalex.org/W2138621811","https://openalex.org/W2155189155","https://openalex.org/W2162237605","https://openalex.org/W2170682668","https://openalex.org/W2181061855","https://openalex.org/W2244619819","https://openalex.org/W2255253409","https://openalex.org/W2343997148","https://openalex.org/W2413424129","https://openalex.org/W2486235263","https://openalex.org/W2565273294","https://openalex.org/W4236780715","https://openalex.org/W4241569833"],"related_works":["https://openalex.org/W2388687352","https://openalex.org/W3008339103","https://openalex.org/W2404647514","https://openalex.org/W2370187191","https://openalex.org/W1667647204","https://openalex.org/W3119814709","https://openalex.org/W2369854048","https://openalex.org/W2374291020","https://openalex.org/W2355907197","https://openalex.org/W3036380379"],"abstract_inverted_index":{"This":[0],"work":[1],"is":[2,59],"motivated":[3],"by":[4,118,242],"the":[5,36,63,68,105,110,113,128,153,158,175,185,239],"need":[6],"to":[7,12,30,61,81,127,135,172],"provide":[8],"reliable":[9],"information":[10],"recommendation":[11],"users":[13],"in":[14,35,56,125,157,225],"social":[15,57],"sensing.":[16],"Social":[17],"sensing":[18,58],"has":[19,235],"become":[20],"an":[21,97],"emerging":[22],"application":[23],"paradigm":[24],"that":[25,150,232],"uses":[26],"humans":[27],"as":[28,46,84,116,182,184],"sensors":[29],"observe":[31],"and":[32,67,133,177,187,212,227,246],"report":[33],"events":[34],"physical":[37],"world.":[38],"These":[39],"human":[40,131],"sensed":[41],"observations":[42],"are":[43],"often":[44],"viewed":[45],"binary":[47],"claims":[48,66,114,181],"(either":[49],"true":[50],"or":[51,137],"false).":[52],"A":[53],"fundamental":[54],"challenge":[55,83],"how":[60],"ascertain":[62],"credibility":[64],"of":[65,70,75,109,130,160,180,190],"reliability":[69,186],"sources":[71,132],"without":[72],"knowing":[73],"either":[74],"them":[76],"a":[77,146,168],"priori.":[78],"We":[79,192],"refer":[80],"this":[82,95,142],"truth":[85,161,198],"discovery.":[86],"While":[87],"prior":[88],"works":[89],"have":[90],"made":[91],"progress":[92],"on":[93],"addressing":[94],"challenge,":[96],"important":[98],"limitation":[99],"exists:":[100],"they":[101],"did":[102],"not":[103],"explore":[104],"mood":[106,129,154,178,188,247],"sensitivity":[107,155,189],"aspect":[108],"problem.":[111,163],"Therefore,":[112],"identified":[115],"correct":[117,245],"current":[119],"solutions":[120,200],"can":[121],"be":[122],"completely":[123],"biased":[124],"regards":[126],"lead":[134],"useless":[136],"even":[138],"misleading":[139],"recommendations.":[140],"In":[141],"paper,":[143],"we":[144],"present":[145],"new":[147,165],"analytical":[148],"model":[149,166,195,234],"explicitly":[151],"considers":[152],"feature":[156],"solution":[159],"discovery":[162,199],"The":[164,229],"solves":[167],"multi-dimensional":[169],"estimation":[170],"problem":[171],"jointly":[173],"estimate":[174],"correctness":[176],"neutrality":[179],"well":[183],"sources.":[191],"compare":[193],"our":[194,233],"with":[196],"state-of-the-art":[197],"using":[201],"four":[202],"real":[203],"world":[204],"datasets":[205],"collected":[206],"from":[207],"Twitter":[208],"during":[209],"recent":[210],"disastrous":[211],"emergent":[213],"events:":[214],"Brussels":[215],"Bombing,":[216],"Paris":[217],"Attack,":[218],"Oregon":[219],"Shooting,":[220],"Baltimore":[221],"Riots,":[222],"which":[223],"occurred":[224],"2015":[226],"2016.":[228],"results":[230],"show":[231],"significant":[236],"improvements":[237],"over":[238],"compared":[240],"baselines":[241],"finding":[243],"more":[244],"neutral":[248],"claims.":[249]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}