{"id":"https://openalex.org/W4402280109","doi":"https://doi.org/10.3390/bdcc8090111","title":"A Data-Centric Approach to Understanding the 2020 U.S. Presidential Election","display_name":"A Data-Centric Approach to Understanding the 2020 U.S. Presidential Election","publication_year":2024,"publication_date":"2024-09-04","ids":{"openalex":"https://openalex.org/W4402280109","doi":"https://doi.org/10.3390/bdcc8090111"},"language":"en","primary_location":{"id":"doi:10.3390/bdcc8090111","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc8090111","pdf_url":null,"source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"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":"Big Data and Cognitive Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/bdcc8090111","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021929717","display_name":"Satish Srinivasan","orcid":"https://orcid.org/0000-0003-1377-3726"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Satish Mahadevan Srinivasan","raw_affiliation_strings":["Engineering Department, Pennsylvania State University, Great Valley, Malvern, PA 19355, USA"],"affiliations":[{"raw_affiliation_string":"Engineering Department, Pennsylvania State University, Great Valley, Malvern, PA 19355, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000525176","display_name":"Yok\u2010Fong Paat","orcid":"https://orcid.org/0000-0001-5791-0791"},"institutions":[{"id":"https://openalex.org/I164936912","display_name":"The University of Texas at El Paso","ror":"https://ror.org/04d5vba33","country_code":"US","type":"education","lineage":["https://openalex.org/I164936912"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yok-Fong Paat","raw_affiliation_strings":["Department of Social Work, The University of Texas at El Paso, El Paso, TX 79968, USA"],"affiliations":[{"raw_affiliation_string":"Department of Social Work, The University of Texas at El Paso, El Paso, TX 79968, USA","institution_ids":["https://openalex.org/I164936912"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5021929717"],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12696715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"9","first_page":"111","last_page":"111"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9883000254631042,"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":0.9883000254631042,"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":0.913100004196167,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/presidential-election","display_name":"Presidential election","score":0.5607500076293945},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.49689748883247375},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.39109545946121216},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.31424373388290405},{"id":"https://openalex.org/keywords/politics","display_name":"Politics","score":0.20273175835609436},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.12018117308616638}],"concepts":[{"id":"https://openalex.org/C2776129789","wikidata":"https://www.wikidata.org/wiki/Q858439","display_name":"Presidential election","level":3,"score":0.5607500076293945},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.49689748883247375},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.39109545946121216},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.31424373388290405},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.20273175835609436},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.12018117308616638}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/bdcc8090111","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc8090111","pdf_url":null,"source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"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":"Big Data and Cognitive Computing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:49c46a3f4cea430d9f0df92cc1c717c1","is_oa":true,"landing_page_url":"https://doaj.org/article/49c46a3f4cea430d9f0df92cc1c717c1","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":"Big Data and Cognitive Computing, Vol 8, Iss 9, p 111 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/bdcc8090111","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc8090111","pdf_url":null,"source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"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":"Big Data and Cognitive Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2402700","https://openalex.org/W30283642","https://openalex.org/W40549020","https://openalex.org/W104683736","https://openalex.org/W135937222","https://openalex.org/W1513398909","https://openalex.org/W2120615054","https://openalex.org/W2124156373","https://openalex.org/W2149628368","https://openalex.org/W2162010436","https://openalex.org/W2162095830","https://openalex.org/W2165113952","https://openalex.org/W2166706824","https://openalex.org/W2167578410","https://openalex.org/W2251939518","https://openalex.org/W2252073650","https://openalex.org/W2262194405","https://openalex.org/W2265846598","https://openalex.org/W2336851846","https://openalex.org/W2462025561","https://openalex.org/W2527727731","https://openalex.org/W2741447225","https://openalex.org/W2759483166","https://openalex.org/W2894267554","https://openalex.org/W2905807898","https://openalex.org/W2918378401","https://openalex.org/W2920808534","https://openalex.org/W2948005942","https://openalex.org/W3092361805","https://openalex.org/W4220818128","https://openalex.org/W4239946314","https://openalex.org/W4283786327","https://openalex.org/W4385734115","https://openalex.org/W6687711781","https://openalex.org/W6691444137","https://openalex.org/W6697146284","https://openalex.org/W6703230933","https://openalex.org/W6754392684","https://openalex.org/W6763261302","https://openalex.org/W7010627773"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"The":[0,174],"application":[1],"of":[2,24,61,129,138,152,166,177,204,209],"analytics":[3],"on":[4,26,48],"Twitter":[5],"feeds":[6],"is":[7],"a":[8,17,22,49,72],"very":[9],"popular":[10],"field":[11],"for":[12,121],"research.":[13],"A":[14],"tweet":[15],"with":[16,186],"280-character":[18],"limitation":[19],"can":[20,53],"reveal":[21],"wealth":[23],"information":[25],"how":[27],"individuals":[28,47],"express":[29],"their":[30,35,122],"sentiments":[31,58,67,99,114,208],"and":[32,42,59,68,98,113,124,159,207,218,227],"emotions":[33,60,69,97,112,206],"within":[34,116],"network":[36],"or":[37],"community.":[38],"Upon":[39],"collecting,":[40],"cleaning,":[41],"mining":[43],"tweets":[44,86,118,179],"from":[45],"different":[46],"particular":[50],"topic,":[51],"we":[52,81,143],"capture":[54],"not":[55],"only":[56],"the":[57,66,76,92,96,105,111,126,136,139,149,164,178,181,187,195,202,205,210],"an":[62],"individual":[63],"but":[64],"also":[65],"expressed":[70,100,115],"by":[71,101],"larger":[73],"group.":[74],"Using":[75],"well-known":[77],"Lexicon-based":[78],"NRC":[79,182],"classifier,":[80],"classified":[82],"nearly":[83],"seven":[84,88],"million":[85],"across":[87],"battleground":[89,131,154],"states":[90,155],"in":[91,169,212],"U.S.":[93,102],"to":[94,135,146,200,230],"understand":[95,201],"citizens":[103],"toward":[104],"2020":[106,140],"presidential":[107,141],"candidates.":[108],"We":[109],"used":[110],"these":[117],"as":[119],"proxies":[120],"votes":[123],"predicted":[125],"swing":[127,150],"directions":[128,151],"each":[130,213],"state.":[132],"When":[133],"compared":[134],"outcome":[137],"candidates,":[142],"were":[144],"able":[145],"accurately":[147],"predict":[148],"four":[153],"(Arizona,":[156],"Michigan,":[157],"Texas,":[158],"North":[160],"Carolina),":[161],"thus":[162],"revealing":[163],"potential":[165],"this":[167],"approach":[168],"predicting":[170],"future":[171],"election":[172,232],"outcomes.":[173,233],"week-by-week":[175],"analysis":[176],"using":[180],"classifier":[183],"corroborated":[184],"well":[185],"various":[188],"political":[189],"events":[190],"that":[191],"took":[192],"place":[193],"before":[194],"election,":[196],"making":[197],"it":[198],"possible":[199],"dynamics":[203],"supporters":[211],"camp.":[214],"These":[215],"research":[216],"strategies":[217],"evidence-based":[219],"insights":[220],"may":[221],"be":[222],"translated":[223],"into":[224],"real-world":[225],"settings":[226],"practical":[228],"interventions":[229],"improve":[231]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}