{"id":"https://openalex.org/W2180879080","doi":"https://doi.org/10.1109/sahcn.2015.7338315","title":"Demo paper: A confidence-aware truth estimation tool for social sensing applications","display_name":"Demo paper: A confidence-aware truth estimation tool for social sensing applications","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W2180879080","doi":"https://doi.org/10.1109/sahcn.2015.7338315","mag":"2180879080"},"language":"en","primary_location":{"id":"doi:10.1109/sahcn.2015.7338315","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sahcn.2015.7338315","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 12th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","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/A5102025799","display_name":"Chao Huang","orcid":"https://orcid.org/0000-0003-0070-2160"},"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":"Chao Huang","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN","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":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102025799"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.08997472,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"20","issue":null,"first_page":"187","last_page":"189"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9998000264167786,"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":0.9998000264167786,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.8784384727478027},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7802444696426392},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6835492253303528},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6727278232574463},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.6613553762435913},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5946657657623291},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5489242672920227},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.45397093892097473},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4178524911403656},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.36869800090789795},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32742947340011597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30739742517471313},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.25062769651412964},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.1331416666507721},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12293872237205505},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0763753354549408}],"concepts":[{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.8784384727478027},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7802444696426392},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6835492253303528},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6727278232574463},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.6613553762435913},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5946657657623291},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5489242672920227},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.45397093892097473},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4178524911403656},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.36869800090789795},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32742947340011597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30739742517471313},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.25062769651412964},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.1331416666507721},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12293872237205505},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0763753354549408},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sahcn.2015.7338315","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sahcn.2015.7338315","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 12th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1565377632","https://openalex.org/W1967647772","https://openalex.org/W1998212475","https://openalex.org/W2009043302","https://openalex.org/W2038946499","https://openalex.org/W2039802096","https://openalex.org/W2051688597","https://openalex.org/W2118388899","https://openalex.org/W2125635328","https://openalex.org/W2131369712","https://openalex.org/W2142687577","https://openalex.org/W2149777147","https://openalex.org/W2155189155","https://openalex.org/W2162555816","https://openalex.org/W2167339613","https://openalex.org/W2181061855","https://openalex.org/W2303140368","https://openalex.org/W2413424129","https://openalex.org/W2482589566","https://openalex.org/W4253271685","https://openalex.org/W4253387571","https://openalex.org/W6697763917"],"related_works":["https://openalex.org/W1667647204","https://openalex.org/W2404647514","https://openalex.org/W4247536566","https://openalex.org/W4241418540","https://openalex.org/W2018477250","https://openalex.org/W3119814709","https://openalex.org/W1508895727","https://openalex.org/W2725786787","https://openalex.org/W1590965489","https://openalex.org/W1875930651"],"abstract_inverted_index":{"This":[0],"paper":[1,9],"presents":[2],"a":[3,24,31,84,87,115],"demonstration":[4],"of":[5,27,33,61,86,98,147],"our":[6],"SECON":[7],"2015":[8],"using":[10],"Twitter":[11,137],"based":[12],"case":[13],"studies":[14],"for":[15],"social":[16,53],"sensing":[17,20,54],"applications.":[18],"Social":[19],"has":[21],"emerged":[22],"as":[23,76],"new":[25,88],"paradigm":[26],"data":[28,66],"collection,":[29],"where":[30],"group":[32],"individuals":[34],"volunteer":[35],"(or":[36],"are":[37],"recruited)":[38],"to":[39,73,117,136],"share":[40],"certain":[41],"observations":[42,63],"or":[43],"measurements":[44],"about":[45],"the":[46,59,104,108,111,121,145],"physical":[47],"world.":[48],"A":[49],"key":[50],"challenge":[51],"in":[52,57,144],"applications":[55],"lies":[56],"ascertaining":[58],"correctness":[60],"reported":[62,105],"from":[64,130],"unvetted":[65],"sources":[67,101],"with":[68,120],"unknown":[69],"reliability.":[70],"We":[71],"refer":[72],"this":[74,80],"problem":[75],"truth":[77,90,141],"estimation.":[78],"In":[79,107],"paper,":[81],"we":[82,127],"showed":[83],"demo":[85,109],"confidence-aware":[89],"estimation":[91,142],"scheme":[92],"that":[93,100],"explicitly":[94],"considers":[95],"different":[96],"degrees":[97],"confidence":[99],"express":[102],"on":[103,123],"data.":[106],"session:":[110],"participants":[112],"will":[113],"have":[114,128],"chance":[116],"(i)":[118],"play":[119],"tool":[122],"some":[124],"historic":[125],"datasets":[126],"collected":[129],"Twitter;":[131],"(ii)":[132],"send":[133],"live":[134],"queries":[135],"and":[138],"perform":[139],"real-time":[140],"analysis":[143],"events":[146],"their":[148],"interests.":[149]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}