{"id":"https://openalex.org/W3108080580","doi":"https://doi.org/10.1109/iwbis50925.2020.9255531","title":"Sentiment Analysis of the Covid-19 Virus Infection in Indonesian Public Transportation on Twitter Data: A Case Study of Commuter Line Passengers","display_name":"Sentiment Analysis of the Covid-19 Virus Infection in Indonesian Public Transportation on Twitter Data: A Case Study of Commuter Line Passengers","publication_year":2020,"publication_date":"2020-10-17","ids":{"openalex":"https://openalex.org/W3108080580","doi":"https://doi.org/10.1109/iwbis50925.2020.9255531","mag":"3108080580"},"language":"en","primary_location":{"id":"doi:10.1109/iwbis50925.2020.9255531","is_oa":true,"landing_page_url":"https://doi.org/10.1109/iwbis50925.2020.9255531","pdf_url":"https://ieeexplore.ieee.org/ielx7/9255449/9255495/09255531.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Workshop on Big Data and Information Security (IWBIS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/9255449/9255495/09255531.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075968593","display_name":"Intania Cahya Sari","orcid":null},"institutions":[{"id":"https://openalex.org/I29617571","display_name":"University of Indonesia","ror":"https://ror.org/0116zj450","country_code":"ID","type":"education","lineage":["https://openalex.org/I29617571"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Intania Cahya Sari","raw_affiliation_strings":["Magister of Technology Information, Universitas Indonesia, Jakarta, Indonesia"],"affiliations":[{"raw_affiliation_string":"Magister of Technology Information, Universitas Indonesia, Jakarta, Indonesia","institution_ids":["https://openalex.org/I29617571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079525306","display_name":"Yova Ruldeviyani","orcid":"https://orcid.org/0000-0002-3051-7540"},"institutions":[{"id":"https://openalex.org/I29617571","display_name":"University of Indonesia","ror":"https://ror.org/0116zj450","country_code":"ID","type":"education","lineage":["https://openalex.org/I29617571"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Yova Ruldeviyani","raw_affiliation_strings":["Magister of Technology Information, Universitas Indonesia, Jakarta, Indonesia"],"affiliations":[{"raw_affiliation_string":"Magister of Technology Information, Universitas Indonesia, Jakarta, Indonesia","institution_ids":["https://openalex.org/I29617571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075968593"],"corresponding_institution_ids":["https://openalex.org/I29617571"],"apc_list":null,"apc_paid":null,"fwci":3.9768,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.94813374,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"23","last_page":"28"},"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/T13728","display_name":"Crime, Deviance, and Social Control","score":0.9711999893188477,"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/T12488","display_name":"Mental Health via Writing","score":0.9581999778747559,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"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":0.6753888130187988},{"id":"https://openalex.org/keywords/pandemic","display_name":"Pandemic","score":0.6210010051727295},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.5373934507369995},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5325761437416077},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5012917518615723},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.48453348875045776},{"id":"https://openalex.org/keywords/worry","display_name":"Worry","score":0.4493553638458252},{"id":"https://openalex.org/keywords/indonesian","display_name":"Indonesian","score":0.42380568385124207},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41013529896736145},{"id":"https://openalex.org/keywords/advertising","display_name":"Advertising","score":0.37053409218788147},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.3410816192626953},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.3360288441181183},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.2588019073009491},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.18782666325569153},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.18764790892601013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18380597233772278},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07351499795913696}],"concepts":[{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6753888130187988},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.6210010051727295},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.5373934507369995},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5325761437416077},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5012917518615723},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.48453348875045776},{"id":"https://openalex.org/C2779978724","wikidata":"https://www.wikidata.org/wiki/Q1436482","display_name":"Worry","level":3,"score":0.4493553638458252},{"id":"https://openalex.org/C2779207338","wikidata":"https://www.wikidata.org/wiki/Q9240","display_name":"Indonesian","level":2,"score":0.42380568385124207},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41013529896736145},{"id":"https://openalex.org/C112698675","wikidata":"https://www.wikidata.org/wiki/Q37038","display_name":"Advertising","level":1,"score":0.37053409218788147},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.3410816192626953},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3360288441181183},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2588019073009491},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.18782666325569153},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.18764790892601013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18380597233772278},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07351499795913696},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C558461103","wikidata":"https://www.wikidata.org/wiki/Q154430","display_name":"Anxiety","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwbis50925.2020.9255531","is_oa":true,"landing_page_url":"https://doi.org/10.1109/iwbis50925.2020.9255531","pdf_url":"https://ieeexplore.ieee.org/ielx7/9255449/9255495/09255531.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Workshop on Big Data and Information Security (IWBIS)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/iwbis50925.2020.9255531","is_oa":true,"landing_page_url":"https://doi.org/10.1109/iwbis50925.2020.9255531","pdf_url":"https://ieeexplore.ieee.org/ielx7/9255449/9255495/09255531.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Workshop on Big Data and Information Security (IWBIS)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8399999737739563,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3108080580.pdf","grobid_xml":"https://content.openalex.org/works/W3108080580.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1487370128","https://openalex.org/W2019759670","https://openalex.org/W2024228866","https://openalex.org/W2097726431","https://openalex.org/W2108646579","https://openalex.org/W2473873820","https://openalex.org/W2514173981","https://openalex.org/W2592419886","https://openalex.org/W2608581744","https://openalex.org/W2942000225","https://openalex.org/W2944670321","https://openalex.org/W2969758095","https://openalex.org/W2977348857","https://openalex.org/W2997416493","https://openalex.org/W3003807992","https://openalex.org/W3131926329","https://openalex.org/W4211186029","https://openalex.org/W4239822620","https://openalex.org/W6629152969","https://openalex.org/W6737236213","https://openalex.org/W6772936878"],"related_works":["https://openalex.org/W2533368584","https://openalex.org/W3143626098","https://openalex.org/W2777027891","https://openalex.org/W3111932749","https://openalex.org/W1540755181","https://openalex.org/W2128849446","https://openalex.org/W2070886976","https://openalex.org/W2071390961","https://openalex.org/W2132532260","https://openalex.org/W2383026120"],"abstract_inverted_index":{"The":[0,18],"appearance":[1],"of":[2,20,27,49,88,125,140,152,157],"the":[3,14,21,47,53,73,77,86,89,111,123,126,146,155,166],"Covid-19":[4,22,74,90,127],"virus":[5,23,75],"in":[6,39,46,57],"early":[7],"2020":[8],"became":[9],"a":[10,117,138,161],"frightening":[11],"pandemic":[12,91],"for":[13],"world,":[15],"including":[16],"Indonesia.":[17],"infection":[19],"was":[24,119,135,160],"rapid":[25],"because":[26],"its":[28],"transmission":[29,87,128],"can":[30,101],"be":[31,102],"through":[32],"human":[33],"contact.":[34],"This":[35,96,133],"condition":[36],"causes":[37,97],"worrying":[38,43],"society.":[40],"Besides,":[41],"these":[42],"also":[44],"occurs":[45],"passenger":[48],"public":[50],"transportation,":[51],"especially":[52],"commuter":[54,68,78,114,130],"line.":[55,79],"Passengers":[56],"large":[58],"numbers":[59],"and":[60],"push":[61],"each":[62],"other":[63,167],"will":[64,71],"cause":[65],"worry":[66],"if":[67],"line":[69,115,131],"passengers":[70,81],"transmit":[72],"to":[76,109,121,129,165],"Many":[80],"write":[82],"their":[83],"opinions":[84,99,112],"about":[85],"on":[92,113],"social":[93],"media":[94],"Twitter.":[95],"various":[98],"that":[100],"positive,":[103],"negative,":[104],"or":[105],"even":[106],"neutral.":[107],"Therefore,":[108],"see":[110],"passengers,":[116],"research":[118,134],"made":[120],"analyze":[122],"sentiment":[124,158],"passengers.":[132],"implemented":[136],"using":[137],"comparison":[139],"2":[141,168],"methods,":[142],"Na\u00efve":[143],"Bayes":[144],"outperformed":[145],"Decision":[147],"Tree":[148],"with":[149],"an":[150],"accuracy":[151],"73.59%.":[153],"Furthermore,":[154],"result":[156],"analysis":[159],"positive":[162],"classification":[163],"compared":[164],"classes.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
