{"id":"https://openalex.org/W4400416032","doi":"https://doi.org/10.3390/info15070393","title":"The Effect of Training Data Size on Disaster Classification from Twitter","display_name":"The Effect of Training Data Size on Disaster Classification from Twitter","publication_year":2024,"publication_date":"2024-07-08","ids":{"openalex":"https://openalex.org/W4400416032","doi":"https://doi.org/10.3390/info15070393"},"language":"en","primary_location":{"id":"doi:10.3390/info15070393","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info15070393","pdf_url":"https://www.mdpi.com/2078-2489/15/7/393/pdf?version=1720420243","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"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":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/15/7/393/pdf?version=1720420243","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085013156","display_name":"Dimitrios Effrosynidis","orcid":"https://orcid.org/0000-0002-6865-5447"},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Dimitrios Effrosynidis","raw_affiliation_strings":["Database & Information Retrieval Research Unit, Department of Electrical & Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Database & Information Retrieval Research Unit, Department of Electrical & Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece","institution_ids":["https://openalex.org/I147962203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057537846","display_name":"Georgios Sylaios","orcid":"https://orcid.org/0000-0003-2327-4015"},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Georgios Sylaios","raw_affiliation_strings":["Lab of Ecological Engineering & Technology, Department of Environmental Engineering, Democritus University of Thrace, 67100 Xanthi, Greece"],"raw_orcid":"https://orcid.org/0000-0003-2327-4015","affiliations":[{"raw_affiliation_string":"Lab of Ecological Engineering & Technology, Department of Environmental Engineering, Democritus University of Thrace, 67100 Xanthi, Greece","institution_ids":["https://openalex.org/I147962203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058891144","display_name":"Avi Arampatzis","orcid":"https://orcid.org/0000-0003-2415-4592"},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Avi Arampatzis","raw_affiliation_strings":["Database & Information Retrieval Research Unit, Department of Electrical & Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece"],"raw_orcid":"https://orcid.org/0000-0003-2415-4592","affiliations":[{"raw_affiliation_string":"Database & Information Retrieval Research Unit, Department of Electrical & Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece","institution_ids":["https://openalex.org/I147962203"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5085013156"],"corresponding_institution_ids":["https://openalex.org/I147962203"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.8318,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.76504394,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"15","issue":"7","first_page":"393","last_page":"393"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9990000128746033,"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":0.9990000128746033,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9904000163078308,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8246426582336426},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7493398785591125},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7283188104629517},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7012947201728821},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.670239269733429},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.629783034324646},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5472908616065979},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.44303134083747864},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.435842901468277},{"id":"https://openalex.org/keywords/multinomial-logistic-regression","display_name":"Multinomial logistic regression","score":0.4192770719528198},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2120901644229889},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.10044139623641968}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8246426582336426},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7493398785591125},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7283188104629517},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7012947201728821},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.670239269733429},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.629783034324646},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5472908616065979},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.44303134083747864},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.435842901468277},{"id":"https://openalex.org/C117568660","wikidata":"https://www.wikidata.org/wiki/Q1650843","display_name":"Multinomial logistic regression","level":2,"score":0.4192770719528198},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2120901644229889},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.10044139623641968}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info15070393","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info15070393","pdf_url":"https://www.mdpi.com/2078-2489/15/7/393/pdf?version=1720420243","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"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":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ba94ffbd7b5c4ab5bc9c8c8e2f6471e4","is_oa":true,"landing_page_url":"https://doaj.org/article/ba94ffbd7b5c4ab5bc9c8c8e2f6471e4","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":"Information, Vol 15, Iss 7, p 393 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info15070393","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info15070393","pdf_url":"https://www.mdpi.com/2078-2489/15/7/393/pdf?version=1720420243","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"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":"Information","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7900000214576721,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G4329690293","display_name":null,"funder_award_id":"H2020-LC-GD-2020-4","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G4643759632","display_name":null,"funder_award_id":"101037643","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G4937468798","display_name":null,"funder_award_id":"H2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5236259172","display_name":null,"funder_award_id":"H2020-LC-GD-2020-4","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G7416235358","display_name":null,"funder_award_id":"H2020-LC-GD-2020","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G7842005466","display_name":null,"funder_award_id":"Horizon 2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8542525639","display_name":"INTEGRATED DigitaL Framework FOR Comprehensive MARITIME DATA AND INFORMATION SERVICES","funder_award_id":"101037643","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"},{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400416032.pdf","grobid_xml":"https://content.openalex.org/works/W4400416032.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W10004740","https://openalex.org/W641710284","https://openalex.org/W2101234009","https://openalex.org/W2130553043","https://openalex.org/W2187303655","https://openalex.org/W2227904035","https://openalex.org/W2287044641","https://openalex.org/W2294345429","https://openalex.org/W2675196597","https://openalex.org/W2732229717","https://openalex.org/W2753546666","https://openalex.org/W2762820840","https://openalex.org/W2798683079","https://openalex.org/W2808079449","https://openalex.org/W2809087994","https://openalex.org/W2887902433","https://openalex.org/W2890000990","https://openalex.org/W2917065785","https://openalex.org/W2927653920","https://openalex.org/W2950015081","https://openalex.org/W2962707464","https://openalex.org/W2981679558","https://openalex.org/W3043010374","https://openalex.org/W3048573458","https://openalex.org/W3082548640","https://openalex.org/W3092786668","https://openalex.org/W3096636506","https://openalex.org/W3126087996","https://openalex.org/W3150521545","https://openalex.org/W3170414516","https://openalex.org/W3175294292","https://openalex.org/W3210474121","https://openalex.org/W4213009331","https://openalex.org/W4226174029","https://openalex.org/W4230674625","https://openalex.org/W4238746485","https://openalex.org/W4252522382","https://openalex.org/W4309213705","https://openalex.org/W4365508917","https://openalex.org/W4379986648","https://openalex.org/W6675354045","https://openalex.org/W6686923621","https://openalex.org/W6847327001","https://openalex.org/W6869608176"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W2905433371","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2888392564","https://openalex.org/W4298369531","https://openalex.org/W3155135229"],"abstract_inverted_index":{"In":[0],"the":[1,35,40,77],"realm":[2],"of":[3,13,29,39,79,95,124,132],"disaster-related":[4],"tweet":[5],"classification,":[6],"this":[7],"study":[8],"presents":[9],"a":[10,72],"comprehensive":[11],"analysis":[12],"various":[14],"machine":[15],"learning":[16],"algorithms,":[17],"shedding":[18],"light":[19],"on":[20,89],"crucial":[21],"factors":[22],"influencing":[23],"algorithm":[24,86],"performance.":[25],"The":[26],"exceptional":[27],"efficacy":[28],"simpler":[30,80],"models":[31,51],"is":[32,92,134],"attributed":[33],"to":[34,44,56],"quality":[36],"and":[37,54,104,127,139],"size":[38,91],"dataset,":[41],"enabling":[42],"them":[43],"discern":[45],"meaningful":[46],"patterns.":[47],"While":[48],"powerful,":[49],"complex":[50],"are":[52],"time-consuming":[53],"prone":[55],"overfitting,":[57],"particularly":[58],"with":[59,117],"smaller":[60],"or":[61],"noisier":[62],"datasets.":[63],"Hyperparameter":[64],"tuning,":[65],"notably":[66],"through":[67],"Bayesian":[68],"optimization,":[69],"emerges":[70],"as":[71],"pivotal":[73],"tool":[74],"for":[75,85,99,107],"enhancing":[76],"performance":[78],"models.":[81],"A":[82,129],"practical":[83],"guideline":[84],"selection":[87],"based":[88],"dataset":[90],"proposed,":[93],"consisting":[94],"Bernoulli":[96],"Naive":[97],"Bayes":[98],"datasets":[100,109],"below":[101],"5000":[102,111],"tweets":[103],"Logistic":[105,114],"Regression":[106,115],"larger":[108],"exceeding":[110],"tweets.":[112],"Notably,":[113],"shines":[116],"20,000":[118],"tweets,":[119],"delivering":[120],"an":[121],"impressive":[122],"combination":[123],"performance,":[125],"speed,":[126],"interpretability.":[128],"further":[130],"improvement":[131],"0.5%":[133],"achieved":[135],"by":[136],"applying":[137],"ensemble":[138],"stacking":[140],"methods.":[141]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T08:27:34.040176","created_date":"2025-10-10T00:00:00"}