{"id":"https://openalex.org/W3136112407","doi":"https://doi.org/10.1109/bigdata50022.2020.9377865","title":"Urban Crowdsensing using Social Media: An Empirical Study on Transformer and Recurrent Neural Networks","display_name":"Urban Crowdsensing using Social Media: An Empirical Study on Transformer and Recurrent Neural Networks","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3136112407","doi":"https://doi.org/10.1109/bigdata50022.2020.9377865","mag":"3136112407"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9377865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9377865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","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/A5041947352","display_name":"Jerome Heng","orcid":null},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Jerome Heng","raw_affiliation_strings":["Information Systems Technology and Design Pillar, Singapore University of Technology and Design"],"affiliations":[{"raw_affiliation_string":"Information Systems Technology and Design Pillar, Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100741943","display_name":"Junhua Liu","orcid":"https://orcid.org/0000-0003-4477-7439"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Junhua Liu","raw_affiliation_strings":["Information Systems Technology and Design Pillar, Singapore University of Technology and Design"],"affiliations":[{"raw_affiliation_string":"Information Systems Technology and Design Pillar, Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005406384","display_name":"Kwan Hui Lim","orcid":"https://orcid.org/0000-0002-4569-0901"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Kwan Hui Lim","raw_affiliation_strings":["Information Systems Technology and Design Pillar, Singapore University of Technology and Design"],"affiliations":[{"raw_affiliation_string":"Information Systems Technology and Design Pillar, Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5041947352"],"corresponding_institution_ids":["https://openalex.org/I152815399"],"apc_list":null,"apc_paid":null,"fwci":0.7689,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.80638787,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"5695","last_page":"5697"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9997000098228455,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9968000054359436,"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/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7936906218528748},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.6919656991958618},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.569589376449585},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5316705703735352},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5242959856987},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5190147161483765},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5110574960708618},{"id":"https://openalex.org/keywords/urban-computing","display_name":"Urban computing","score":0.5008032321929932},{"id":"https://openalex.org/keywords/crowdsensing","display_name":"Crowdsensing","score":0.4837753474712372},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.47358638048171997},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.4306713044643402},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.42557352781295776},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.42130860686302185},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4178239703178406},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.330438494682312},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.1318719983100891},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10763850808143616},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08521273732185364}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7936906218528748},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.6919656991958618},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.569589376449585},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5316705703735352},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5242959856987},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5190147161483765},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5110574960708618},{"id":"https://openalex.org/C2778459138","wikidata":"https://www.wikidata.org/wiki/Q7900107","display_name":"Urban computing","level":2,"score":0.5008032321929932},{"id":"https://openalex.org/C2780821482","wikidata":"https://www.wikidata.org/wiki/Q25381721","display_name":"Crowdsensing","level":2,"score":0.4837753474712372},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.47358638048171997},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.4306713044643402},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.42557352781295776},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.42130860686302185},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4178239703178406},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.330438494682312},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1318719983100891},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10763850808143616},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08521273732185364},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9377865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9377865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320324110","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1930967223","https://openalex.org/W2061946444","https://openalex.org/W2064675550","https://openalex.org/W2118978333","https://openalex.org/W2157331557","https://openalex.org/W2250539671","https://openalex.org/W2401891380","https://openalex.org/W2622833445","https://openalex.org/W2908939884","https://openalex.org/W2911376306","https://openalex.org/W2963840760","https://openalex.org/W2978017171","https://openalex.org/W3098230111","https://openalex.org/W3134022035","https://openalex.org/W3136082951","https://openalex.org/W4243367342","https://openalex.org/W6768851824","https://openalex.org/W6779216831"],"related_works":["https://openalex.org/W3032998312","https://openalex.org/W135177976","https://openalex.org/W2896200027","https://openalex.org/W2904716865","https://openalex.org/W4386076228","https://openalex.org/W4310825149","https://openalex.org/W2954450070","https://openalex.org/W2798269247","https://openalex.org/W2761749530","https://openalex.org/W1935670169"],"abstract_inverted_index":{"An":[0],"important":[1],"aspect":[2],"of":[3,18,67,86,98],"urban":[4,54],"planning":[5],"is":[6,70,109],"understanding":[7],"crowd":[8,61,127],"levels":[9],"at":[10],"various":[11],"locations,":[12],"which":[13],"typically":[14],"require":[15],"the":[16,50,84],"use":[17,47],"physical":[19],"sensors.":[20],"Such":[21],"sensors":[22],"are":[23],"potentially":[24],"costly":[25],"and":[26,46,60,76,114,136],"time":[27],"consuming":[28],"to":[29,102,111,124],"implement":[30],"on":[31],"a":[32,96,105,116],"large":[33],"scale.":[34],"To":[35],"address":[36],"this":[37,68,87],"issue,":[38],"we":[39],"utilize":[40],"publicly":[41],"available":[42],"social":[43,106,120],"media":[44,107,121],"datasets":[45],"them":[48],"as":[49],"basis":[51],"for":[52],"two":[53,90],"sensing":[55],"problems,":[56],"namely":[57],"event":[58,113],"detection":[59],"level":[62],"prediction.":[63],"One":[64],"main":[65],"contribution":[66],"work":[69],"our":[71],"collected":[72],"dataset":[73,88],"from":[74,133],"Twitter":[75],"Flickr,":[77],"alongside":[78],"ground":[79],"truth":[80],"events.":[81],"We":[82,129],"demonstrate":[83],"usefulness":[85],"with":[89],"preliminary":[91,131],"supervised":[92],"learning":[93],"approaches:":[94],"firstly,":[95],"series":[97],"neural":[99],"network":[100],"models":[101],"determine":[103],"if":[104],"post":[108,122],"related":[110],"an":[112],"secondly":[115],"regression":[117],"model":[118],"using":[119],"counts":[123],"predict":[125],"actual":[126],"levels.":[128],"discuss":[130],"results":[132],"these":[134],"tasks":[135],"highlight":[137],"some":[138],"challenges.":[139]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}