{"id":"https://openalex.org/W4283652145","doi":"https://doi.org/10.1186/s40537-022-00636-w","title":"Deep-Eware: spatio-temporal social event detection using a hybrid learning model","display_name":"Deep-Eware: spatio-temporal social event detection using a hybrid learning model","publication_year":2022,"publication_date":"2022-06-28","ids":{"openalex":"https://openalex.org/W4283652145","doi":"https://doi.org/10.1186/s40537-022-00636-w","pmid":"https://pubmed.ncbi.nlm.nih.gov/35789805"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-022-00636-w","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00636-w","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00636-w","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00636-w","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000538231","display_name":"Imad Afyouni","orcid":"https://orcid.org/0000-0001-6686-3069"},"institutions":[{"id":"https://openalex.org/I29891158","display_name":"University of Sharjah","ror":"https://ror.org/00engpz63","country_code":"AE","type":"education","lineage":["https://openalex.org/I29891158"]}],"countries":["AE"],"is_corresponding":true,"raw_author_name":"Imad Afyouni","raw_affiliation_strings":["University of Sharjah, Sharjah, United Arab Emirates"],"affiliations":[{"raw_affiliation_string":"University of Sharjah, Sharjah, United Arab Emirates","institution_ids":["https://openalex.org/I29891158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051789165","display_name":"Aamir Khan","orcid":null},"institutions":[{"id":"https://openalex.org/I29891158","display_name":"University of Sharjah","ror":"https://ror.org/00engpz63","country_code":"AE","type":"education","lineage":["https://openalex.org/I29891158"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Aamir Khan","raw_affiliation_strings":["University of Sharjah, Sharjah, United Arab Emirates"],"affiliations":[{"raw_affiliation_string":"University of Sharjah, Sharjah, United Arab Emirates","institution_ids":["https://openalex.org/I29891158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069814126","display_name":"Zaher Al Aghbari","orcid":"https://orcid.org/0000-0003-2285-953X"},"institutions":[{"id":"https://openalex.org/I29891158","display_name":"University of Sharjah","ror":"https://ror.org/00engpz63","country_code":"AE","type":"education","lineage":["https://openalex.org/I29891158"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Zaher Al Aghbari","raw_affiliation_strings":["University of Sharjah, Sharjah, United Arab Emirates"],"affiliations":[{"raw_affiliation_string":"University of Sharjah, Sharjah, United Arab Emirates","institution_ids":["https://openalex.org/I29891158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000538231"],"corresponding_institution_ids":["https://openalex.org/I29891158"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":5.0869,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.94414208,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"9","issue":"1","first_page":"86","last_page":"86"},"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":0.996399998664856,"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":0.996399998664856,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9878000020980835,"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/T10757","display_name":"Geographic Information Systems Studies","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8447616100311279},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.679320216178894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6478719711303711},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6451295018196106},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5631588697433472},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5112323760986328},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4920651316642761},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.486465185880661},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.46665143966674805},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.45570334792137146},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4538118541240692},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4205875098705292},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.41100651025772095},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39098984003067017},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12239187955856323}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8447616100311279},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.679320216178894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6478719711303711},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6451295018196106},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5631588697433472},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5112323760986328},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4920651316642761},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.486465185880661},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.46665143966674805},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.45570334792137146},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4538118541240692},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4205875098705292},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.41100651025772095},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39098984003067017},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12239187955856323},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1186/s40537-022-00636-w","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00636-w","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00636-w","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmid:35789805","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35789805","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of big data","raw_type":null},{"id":"pmh:oai:doaj.org/article:75abcb4c40b84c53acc21f8a686593b3","is_oa":true,"landing_page_url":"https://doaj.org/article/75abcb4c40b84c53acc21f8a686593b3","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 9, Iss 1, Pp 1-21 (2022)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:9243793","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9243793","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Big Data","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s40537-022-00636-w","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00636-w","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00636-w","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4283652145.pdf","grobid_xml":"https://content.openalex.org/works/W4283652145.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1890727290","https://openalex.org/W2008607062","https://openalex.org/W2073545563","https://openalex.org/W2109722477","https://openalex.org/W2273718352","https://openalex.org/W2295338537","https://openalex.org/W2599584741","https://openalex.org/W2737381691","https://openalex.org/W2763211776","https://openalex.org/W2794800729","https://openalex.org/W2798037494","https://openalex.org/W2896443452","https://openalex.org/W2901190688","https://openalex.org/W2914761964","https://openalex.org/W2926283842","https://openalex.org/W2962686197","https://openalex.org/W2963840760","https://openalex.org/W2974476431","https://openalex.org/W2981219037","https://openalex.org/W2981733944","https://openalex.org/W2987141572","https://openalex.org/W3006943951","https://openalex.org/W3008268504","https://openalex.org/W3008585262","https://openalex.org/W3010403975","https://openalex.org/W3033087404","https://openalex.org/W3039718336","https://openalex.org/W3098230111","https://openalex.org/W3121835124","https://openalex.org/W3130808434","https://openalex.org/W3152497081","https://openalex.org/W3211643415","https://openalex.org/W4220986946","https://openalex.org/W4252250696"],"related_works":["https://openalex.org/W4367313141","https://openalex.org/W2004086023","https://openalex.org/W2733999579","https://openalex.org/W2110217573","https://openalex.org/W4283374591","https://openalex.org/W2910751785","https://openalex.org/W4362512700","https://openalex.org/W4366547507","https://openalex.org/W4390608645","https://openalex.org/W4390100400"],"abstract_inverted_index":{"Event":[0,139],"detection":[1,193],"from":[2,38,196],"social":[3,36,40,197],"media":[4],"aims":[5],"at":[6],"extracting":[7],"specific":[8],"or":[9],"generic":[10],"unusual":[11],"happenings,":[12],"such":[13,209],"as,":[14],"family":[15],"reunions,":[16],"earthquakes,":[17],"and":[18,33,59,78,88,96,115,118,123,145,169,194,217],"disease":[19,215],"outbreaks,":[20],"among":[21],"others.":[22],"This":[23,199],"paper":[24],"introduces":[25],"a":[26,46,76,103,129,186],"new":[27],"perspective":[28],"for":[29,56,92,107,136,155,181,189],"the":[30,70,93,167,202],"hybrid":[31,47,94,179],"extraction":[32,58,95,184],"clustering":[34,65,152],"of":[35,98,157,171,204],"events":[37],"big":[39,81],"data":[41,82,86],"streams.":[42],"We":[43,73,101,159],"rely":[44],"on":[45],"learning":[48,53,114],"model,":[49],"where":[50],"supervised":[51],"deep":[52],"is":[54,66,141],"used":[55,154],"feature":[57],"topic":[60],"classification,":[61],"whereas":[62],"unsupervised":[63,112],"spatial":[64,124,151],"employed":[67],"to":[68,165,201],"determine":[69],"event":[71,108,183,192],"whereabouts.":[72],"present":[74],"<i>'Deep-Eware'</i>,":[75],"scalable":[77],"efficient":[79],"event-aware":[80],"platform":[83],"that":[84,177],"integrates":[85,128],"stream":[87],"geospatial":[89],"processing":[90],"tools":[91],"dissemination":[97],"spatio-temporal":[99,182,191],"events.":[100,158],"introduce":[102],"pure":[104],"incremental":[105],"approach":[106,180],"discovery,":[109],"by":[110,119],"developing":[111],"machine":[113],"NLP":[116],"algorithms":[117],"computing":[120],"events'":[121],"lifetime":[122],"spanning.":[125],"The":[126,174],"system":[127],"semantic":[130],"keyword":[131],"generation":[132],"tool":[133],"using":[134,143],"KeyBERT":[135],"dataset":[137],"preparation.":[138],"classification":[140],"performed":[142],"CNN":[144],"bidirectional":[146],"LSTM,":[147],"while":[148],"hierarchical":[149],"density-based":[150],"was":[153],"location-inference":[156],"conduct":[160],"experiments":[161],"over":[162],"Twitter":[163],"datasets":[164],"measure":[166],"effectiveness":[168],"efficiency":[170],"our":[172],"system.":[173],"results":[175],"demonstrate":[176],"this":[178],"has":[185],"major":[187],"advantage":[188],"real-time":[190],"tracking":[195],"media.":[198],"leads":[200],"development":[203],"unparalleled":[205],"smart":[206],"city":[207],"applications,":[208],"as":[210],"event-enriched":[211],"trip":[212],"planning,":[213],"epidemic":[214],"evolution,":[216],"proactive":[218],"emergency":[219],"management":[220],"services.":[221]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":7}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}