{"id":"https://openalex.org/W4389481553","doi":"https://doi.org/10.3390/informatics10040088","title":"Unraveling Microblog Sentiment Dynamics: A Twitter Public Attitudes Analysis towards COVID-19 Cases and Deaths","display_name":"Unraveling Microblog Sentiment Dynamics: A Twitter Public Attitudes Analysis towards COVID-19 Cases and Deaths","publication_year":2023,"publication_date":"2023-12-07","ids":{"openalex":"https://openalex.org/W4389481553","doi":"https://doi.org/10.3390/informatics10040088"},"language":"en","primary_location":{"id":"doi:10.3390/informatics10040088","is_oa":true,"landing_page_url":"https://doi.org/10.3390/informatics10040088","pdf_url":"https://www.mdpi.com/2227-9709/10/4/88/pdf?version=1702030788","source":{"id":"https://openalex.org/S2738238905","display_name":"Informatics","issn_l":"2227-9709","issn":["2227-9709"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2227-9709/10/4/88/pdf?version=1702030788","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077173629","display_name":"Paraskevas Koukaras","orcid":"https://orcid.org/0000-0002-1183-9878"},"institutions":[{"id":"https://openalex.org/I183898223","display_name":"International Hellenic University","ror":"https://ror.org/00708jp83","country_code":"GR","type":"education","lineage":["https://openalex.org/I183898223"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Paraskevas Koukaras","raw_affiliation_strings":["School of Science and Technology, International Hellenic University, 57001 Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0002-1183-9878","affiliations":[{"raw_affiliation_string":"School of Science and Technology, International Hellenic University, 57001 Thessaloniki, Greece","institution_ids":["https://openalex.org/I183898223"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036161801","display_name":"Dimitrios Rousidis","orcid":"https://orcid.org/0000-0003-0632-9731"},"institutions":[{"id":"https://openalex.org/I183898223","display_name":"International Hellenic University","ror":"https://ror.org/00708jp83","country_code":"GR","type":"education","lineage":["https://openalex.org/I183898223"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Dimitrios Rousidis","raw_affiliation_strings":["School of Science and Technology, International Hellenic University, 57001 Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0003-0632-9731","affiliations":[{"raw_affiliation_string":"School of Science and Technology, International Hellenic University, 57001 Thessaloniki, Greece","institution_ids":["https://openalex.org/I183898223"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071901091","display_name":"Christos Tjortjis","orcid":"https://orcid.org/0000-0001-8263-9024"},"institutions":[{"id":"https://openalex.org/I183898223","display_name":"International Hellenic University","ror":"https://ror.org/00708jp83","country_code":"GR","type":"education","lineage":["https://openalex.org/I183898223"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Christos Tjortjis","raw_affiliation_strings":["School of Science and Technology, International Hellenic University, 57001 Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0001-8263-9024","affiliations":[{"raw_affiliation_string":"School of Science and Technology, International Hellenic University, 57001 Thessaloniki, Greece","institution_ids":["https://openalex.org/I183898223"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5071901091"],"corresponding_institution_ids":["https://openalex.org/I183898223"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":1.1264,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.84874053,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"10","issue":"4","first_page":"88","last_page":"88"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9998999834060669,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9959999918937683,"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/T10410","display_name":"COVID-19 epidemiological studies","score":0.9868999719619751,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.783701479434967},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.7761661410331726},{"id":"https://openalex.org/keywords/microblogging","display_name":"Microblogging","score":0.752589225769043},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.46816253662109375},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.4594716429710388},{"id":"https://openalex.org/keywords/misinformation","display_name":"Misinformation","score":0.4356822967529297},{"id":"https://openalex.org/keywords/turkish","display_name":"Turkish","score":0.4321087896823883},{"id":"https://openalex.org/keywords/lexical-analysis","display_name":"Lexical analysis","score":0.4166424870491028},{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.4155125021934509},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3596445918083191},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3242153525352478},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.32140570878982544},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.26164475083351135},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.2432093322277069},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.1595841348171234},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.1272643506526947},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12117716670036316},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11900928616523743},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.11379292607307434},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.08669862151145935}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.783701479434967},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7761661410331726},{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.752589225769043},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.46816253662109375},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.4594716429710388},{"id":"https://openalex.org/C2776990098","wikidata":"https://www.wikidata.org/wiki/Q13579947","display_name":"Misinformation","level":2,"score":0.4356822967529297},{"id":"https://openalex.org/C2781121862","wikidata":"https://www.wikidata.org/wiki/Q256","display_name":"Turkish","level":2,"score":0.4321087896823883},{"id":"https://openalex.org/C176982825","wikidata":"https://www.wikidata.org/wiki/Q835922","display_name":"Lexical analysis","level":2,"score":0.4166424870491028},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.4155125021934509},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3596445918083191},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3242153525352478},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.32140570878982544},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.26164475083351135},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2432093322277069},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1595841348171234},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.1272643506526947},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12117716670036316},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11900928616523743},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.11379292607307434},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.08669862151145935},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/informatics10040088","is_oa":true,"landing_page_url":"https://doi.org/10.3390/informatics10040088","pdf_url":"https://www.mdpi.com/2227-9709/10/4/88/pdf?version=1702030788","source":{"id":"https://openalex.org/S2738238905","display_name":"Informatics","issn_l":"2227-9709","issn":["2227-9709"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e320b742672a4d13b5cc9de9c0c6fc5e","is_oa":true,"landing_page_url":"https://doaj.org/article/e320b742672a4d13b5cc9de9c0c6fc5e","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":"Informatics, Vol 10, Iss 4, p 88 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/informatics10040088","is_oa":true,"landing_page_url":"https://doi.org/10.3390/informatics10040088","pdf_url":"https://www.mdpi.com/2227-9709/10/4/88/pdf?version=1702030788","source":{"id":"https://openalex.org/S2738238905","display_name":"Informatics","issn_l":"2227-9709","issn":["2227-9709"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatics","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G6870533126","display_name":null,"funder_award_id":"2014-2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389481553.pdf","grobid_xml":"https://content.openalex.org/works/W4389481553.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1559426636","https://openalex.org/W2058806401","https://openalex.org/W2109634664","https://openalex.org/W2117332520","https://openalex.org/W2137036358","https://openalex.org/W2793642340","https://openalex.org/W2925120686","https://openalex.org/W3002494277","https://openalex.org/W3011345566","https://openalex.org/W3012983039","https://openalex.org/W3015218641","https://openalex.org/W3015705600","https://openalex.org/W3020349211","https://openalex.org/W3037784022","https://openalex.org/W3043013845","https://openalex.org/W3043095242","https://openalex.org/W3045984998","https://openalex.org/W3048848247","https://openalex.org/W3098431883","https://openalex.org/W3101739755","https://openalex.org/W3103653536","https://openalex.org/W3118455546","https://openalex.org/W3130225900","https://openalex.org/W3131836167","https://openalex.org/W3186253370","https://openalex.org/W3207714266","https://openalex.org/W4205184193","https://openalex.org/W4206233629","https://openalex.org/W4237672341","https://openalex.org/W4239946314","https://openalex.org/W4252695905","https://openalex.org/W4285065125","https://openalex.org/W4285066413","https://openalex.org/W4386072763","https://openalex.org/W6780719967"],"related_works":["https://openalex.org/W3197131596","https://openalex.org/W4390616380","https://openalex.org/W4388666321","https://openalex.org/W4205914924","https://openalex.org/W2962981892","https://openalex.org/W1540611520","https://openalex.org/W3158961892","https://openalex.org/W4235312256","https://openalex.org/W4386885143","https://openalex.org/W4387272222"],"abstract_inverted_index":{"The":[0,53,97,129],"identification":[1],"and":[2,15,65,87,92,118,123,138,145,183,186,192],"analysis":[3,45,110,120],"of":[4,40,58,90,159],"sentiment":[5,24,44,86,108,136,170],"polarity":[6,137,182,191],"in":[7,25,51],"microblog":[8],"data":[9],"has":[10],"drawn":[11],"increased":[12,157],"attention.":[13],"Researchers":[14],"practitioners":[16],"attempt":[17],"to":[18,27,33,95,125,148,156],"extract":[19],"knowledge":[20],"by":[21,42,165],"evaluating":[22],"public":[23,35,85],"response":[26],"global":[28],"events.":[29],"This":[30],"study":[31],"aimed":[32],"evaluate":[34],"attitudes":[36],"towards":[37],"the":[38,56,88,127],"spread":[39],"COVID-19":[41,179],"performing":[43],"on":[46],"over":[47],"2.1":[48],"million":[49],"tweets":[50,167],"English.":[52],"implications":[54],"included":[55],"generation":[57],"insights":[59],"for":[60],"timely":[61],"disease":[62],"outbreak":[63],"prediction":[64],"assertions":[66],"regarding":[67],"worldwide":[68],"events,":[69],"which":[70],"can":[71],"help":[72],"policymakers":[73],"take":[74],"suitable":[75],"actions.":[76],"We":[77,172],"investigated":[78],"whether":[79],"there":[80],"was":[81],"a":[82,133,175,187],"correlation":[83,134,177,189],"between":[84,135,178,190],"number":[89],"cases":[91,185],"deaths":[93,161],"attributed":[94],"COVID-19.":[96],"research":[98],"design":[99],"integrated":[100],"text":[101],"preprocessing":[102],"(regular":[103],"expression":[104],"operations,":[105],"(de)tokenization,":[106],"stopwords),":[107],"polarization":[109],"via":[111],"TextBlob,":[112],"hypothesis":[113,116],"formulation":[114],"(null":[115],"testing),":[117],"statistical":[119],"(Pearson":[121],"coefficient":[122],"p-value)":[124],"produce":[126],"results.":[128],"key":[130],"findings":[131],"highlight":[132],"deaths,":[139],"starting":[140],"at":[141],"41":[142],"days":[143,150,164],"before":[144],"expanding":[146],"up":[147],"3":[149],"after":[151,162],"counting.":[152],"Twitter":[153,180],"users":[154],"reacted":[155],"numbers":[158],"COVID-19-related":[160],"four":[163],"posting":[166],"with":[168],"fading":[169],"polarization.":[171],"also":[173],"detected":[174],"strong":[176],"conversation":[181],"reported":[184,193],"weak":[188],"deaths.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}