{"id":"https://openalex.org/W4403059176","doi":"https://doi.org/10.1080/10095020.2024.2408343","title":"An attention-based hybrid model for spatial and temporal sentiment analysis of COVID-19 related tweets in the contiguous United States","display_name":"An attention-based hybrid model for spatial and temporal sentiment analysis of COVID-19 related tweets in the contiguous United States","publication_year":2024,"publication_date":"2024-10-02","ids":{"openalex":"https://openalex.org/W4403059176","doi":"https://doi.org/10.1080/10095020.2024.2408343"},"language":"en","primary_location":{"id":"doi:10.1080/10095020.2024.2408343","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10095020.2024.2408343","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10095020.2024.2408343?needAccess=true","source":{"id":"https://openalex.org/S36798160","display_name":"Geo-spatial Information Science","issn_l":"1009-5020","issn":["1009-5020","1993-5153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Geo-spatial Information Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/10095020.2024.2408343?needAccess=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000632849","display_name":"Bingnan Li","orcid":"https://orcid.org/0000-0003-3417-3295"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Bingnan Li","raw_affiliation_strings":["University of New South Wales","Kirby Institute, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia"],"raw_orcid":"https://orcid.org/0000-0003-3417-3295","affiliations":[{"raw_affiliation_string":"University of New South Wales","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"Kirby Institute, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078415942","display_name":"Danielle Hutchinson","orcid":"https://orcid.org/0000-0002-5816-6738"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Danielle Hutchinson","raw_affiliation_strings":["University of New South Wales","Kirby Institute, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia"],"raw_orcid":"https://orcid.org/0000-0002-5816-6738","affiliations":[{"raw_affiliation_string":"University of New South Wales","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"Kirby Institute, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077603565","display_name":"Samsung Lim","orcid":"https://orcid.org/0000-0001-9838-8960"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Samsung Lim","raw_affiliation_strings":["University of New South Wales","Kirby Institute, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia","School of Civil and Environmental Engineering, University of New South Wales, Sydney, Australia"],"raw_orcid":"https://orcid.org/0000-0001-9838-8960","affiliations":[{"raw_affiliation_string":"University of New South Wales","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"Kirby Institute, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"School of Civil and Environmental Engineering, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075730026","display_name":"C. Raina MacIntyre","orcid":"https://orcid.org/0000-0002-3060-0555"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Chandini Raina MacIntyre","raw_affiliation_strings":["University of New South Wales","Kirby Institute, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia"],"raw_orcid":"https://orcid.org/0000-0002-3060-0555","affiliations":[{"raw_affiliation_string":"University of New South Wales","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"Kirby Institute, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5077603565"],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":{"value":1625,"currency":"GBP","value_usd":1993},"apc_paid":{"value":1625,"currency":"GBP","value_usd":1993},"fwci":1.2108,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.82283768,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"28","issue":"4","first_page":"1846","last_page":"1865"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9869999885559082,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.9842000007629395,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.7786355018615723},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6881670355796814},{"id":"https://openalex.org/keywords/2019-20-coronavirus-outbreak","display_name":"2019-20 coronavirus outbreak","score":0.4606689214706421},{"id":"https://openalex.org/keywords/severe-acute-respiratory-syndrome-coronavirus-2","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","score":0.4373731017112732},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4088618755340576},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3584745526313782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32350262999534607},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1795160472393036},{"id":"https://openalex.org/keywords/virology","display_name":"Virology","score":0.15152698755264282},{"id":"https://openalex.org/keywords/outbreak","display_name":"Outbreak","score":0.08686348795890808}],"concepts":[{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.7786355018615723},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6881670355796814},{"id":"https://openalex.org/C3006700255","wikidata":"https://www.wikidata.org/wiki/Q81068910","display_name":"2019-20 coronavirus outbreak","level":3,"score":0.4606689214706421},{"id":"https://openalex.org/C3007834351","wikidata":"https://www.wikidata.org/wiki/Q82069695","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","level":5,"score":0.4373731017112732},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4088618755340576},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3584745526313782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32350262999534607},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1795160472393036},{"id":"https://openalex.org/C159047783","wikidata":"https://www.wikidata.org/wiki/Q7215","display_name":"Virology","level":1,"score":0.15152698755264282},{"id":"https://openalex.org/C116675565","wikidata":"https://www.wikidata.org/wiki/Q3241045","display_name":"Outbreak","level":2,"score":0.08686348795890808},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/10095020.2024.2408343","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10095020.2024.2408343","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10095020.2024.2408343?needAccess=true","source":{"id":"https://openalex.org/S36798160","display_name":"Geo-spatial Information Science","issn_l":"1009-5020","issn":["1009-5020","1993-5153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Geo-spatial Information Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8d35fb66dc9442fb9fe02d2918522d17","is_oa":true,"landing_page_url":"https://doaj.org/article/8d35fb66dc9442fb9fe02d2918522d17","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Geo-spatial Information Science, Vol 28, Iss 4, Pp 1846-1865 (2025)","raw_type":"article"},{"id":"pmh:oai:unsworks.library.unsw.edu.au:1959.4/103592","is_oa":true,"landing_page_url":"http://hdl.handle.net/1959.4/103592","pdf_url":null,"source":{"id":"https://openalex.org/S4306401737","display_name":"UNSWorks (University of New South Wales, Sydney, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40053085","host_organization_name":"Australian Defence Force Academy","host_organization_lineage":["https://openalex.org/I40053085"],"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":"Geo Spatial Information Science, 28, 4, 1846-1865","raw_type":"http://purl.org/coar/resource_type/c_6501"}],"best_oa_location":{"id":"doi:10.1080/10095020.2024.2408343","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10095020.2024.2408343","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10095020.2024.2408343?needAccess=true","source":{"id":"https://openalex.org/S36798160","display_name":"Geo-spatial Information Science","issn_l":"1009-5020","issn":["1009-5020","1993-5153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Geo-spatial Information Science","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320315885","display_name":"Australian Government","ror":"https://ror.org/0314h5y94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403059176.pdf","grobid_xml":"https://content.openalex.org/works/W4403059176.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W947140380","https://openalex.org/W2025478229","https://openalex.org/W2048018384","https://openalex.org/W2064675550","https://openalex.org/W2079735306","https://openalex.org/W2082609157","https://openalex.org/W2099813784","https://openalex.org/W2139188905","https://openalex.org/W2158139315","https://openalex.org/W2554720547","https://openalex.org/W2562607067","https://openalex.org/W2733628661","https://openalex.org/W2746802549","https://openalex.org/W2899723212","https://openalex.org/W2914767245","https://openalex.org/W2938211346","https://openalex.org/W2993821971","https://openalex.org/W3026887460","https://openalex.org/W3027403514","https://openalex.org/W3034870045","https://openalex.org/W3043013845","https://openalex.org/W3084388756","https://openalex.org/W3088352144","https://openalex.org/W3090154305","https://openalex.org/W3120829418","https://openalex.org/W3121430869","https://openalex.org/W3124218260","https://openalex.org/W3124516888","https://openalex.org/W3127056209","https://openalex.org/W3146682110","https://openalex.org/W3153484755","https://openalex.org/W3160646055","https://openalex.org/W3164681365","https://openalex.org/W3176189029","https://openalex.org/W3176969785","https://openalex.org/W3181139812","https://openalex.org/W3196064124","https://openalex.org/W4210584262","https://openalex.org/W4285178246","https://openalex.org/W4289261501","https://openalex.org/W4294646788","https://openalex.org/W4309782698","https://openalex.org/W6748002556"],"related_works":["https://openalex.org/W3036314732","https://openalex.org/W3009669391","https://openalex.org/W3176864053","https://openalex.org/W4206669628","https://openalex.org/W3171943759","https://openalex.org/W4292098121","https://openalex.org/W3154141118","https://openalex.org/W4388896133","https://openalex.org/W3031607536","https://openalex.org/W4205317059"],"abstract_inverted_index":{"Understanding":[0],"the":[1,33,83,97,133,136,141,149,155,166,170,174,182,187,200,216,233],"sentiments":[2,122],"of":[3,19,30,47,56,96,173,190,223,229],"social":[4],"media":[5],"posts":[6],"can":[7,139,152,164,179],"help":[8],"health":[9],"authorities":[10],"respond":[11],"to":[12,44,119,207],"disease":[13,58],"outbreaks,":[14],"through":[15,32],"a":[16,28,38,101,226],"proxy":[17],"measure":[18],"fear,":[20],"confidence,":[21],"and":[22,36,60,79,89,103,126,148,157,186,203,225],"community":[23],"compliance.":[24],"Sentiment":[25],"analysis":[26,95],"identifies":[27],"pattern":[29],"emotion":[31],"written":[34],"word":[35],"assigns":[37],"positive,":[39,124],"neutral,":[40,125],"or":[41],"negative":[42,127],"value":[43],"it.":[45],"As":[46],"February":[48],"2023,":[49],"there":[50],"were":[51,74,92,194],"677.7":[52],"million":[53,64],"confirmed":[54,65],"cases":[55],"coronavirus":[57],"(COVID-19)":[59],"more":[61],"than":[62],"6.7":[63],"deaths.":[66],"In":[67,132],"this":[68],"paper,":[69],"around":[70],"170,000":[71],"COVID-19-related":[72,130,197],"tweets":[73,198],"collected":[75,98],"between":[76],"September":[77],"2020":[78],"January":[80],"2021":[81],"in":[82],"contiguous":[84],"United":[85],"States.":[86],"Data":[87],"preprocessing":[88],"exploratory":[90],"investigation":[91],"completed":[93],"for":[94],"dataset.":[99],"Further,":[100],"novel":[102],"unified":[104],"architecture":[105],"called":[106],"attention-based":[107],"one-dimensional":[108],"convolution":[109],"with":[110],"bidirectional":[111],"long":[112],"short-term":[113],"memory":[114],"layers":[115],"(CNN-BiLSTM-ATT)":[116],"is":[117],"proposed":[118,177,201],"classify":[120],"people\u2019s":[121],"as":[123],"based":[128],"on":[129,196],"tweets.":[131],"CNN-BiLSTM-ATT":[134,217],"model,":[135],"CNN":[137],"layer":[138,151,172],"extract":[140,153,180],"low-level":[142],"semantic":[143],"features":[144],"from":[145,169],"textual":[146],"data,":[147],"BiLSTM":[150],"both":[154,181],"previous":[156],"future":[158],"contextual":[159],"representations.":[160],"The":[161,176],"attention":[162],"module":[163],"improve":[165],"information":[167],"focus":[168],"outputted":[171],"BiLSTM.":[175],"method":[178,202],"local":[183],"phrase":[184],"representations":[185],"global":[188],"feature":[189],"sentences.":[191],"Numerical":[192],"experiments":[193],"conducted":[195],"using":[199],"other":[204],"baseline":[205,234],"models":[206],"compare":[208],"their":[209],"performances.":[210],"Our":[211],"experimental":[212],"results":[213],"demonstrate":[214],"that":[215],"model":[218],"achieves":[219],"an":[220],"average":[221],"accuracy":[222],"95.16%":[224],"macro-average":[227],"F1-score":[228],"95.12%,":[230],"which":[231],"outperforms":[232],"models.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-27T08:26:11.824852","created_date":"2025-10-10T00:00:00"}
