{"id":"https://openalex.org/W2953894827","doi":"https://doi.org/10.1142/s0219649219500138","title":"TwitSenti: A Real-Time Twitter Sentiment Analysis and Visualization Framework","display_name":"TwitSenti: A Real-Time Twitter Sentiment Analysis and Visualization Framework","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2953894827","doi":"https://doi.org/10.1142/s0219649219500138","mag":"2953894827"},"language":"en","primary_location":{"id":"doi:10.1142/s0219649219500138","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219649219500138","pdf_url":null,"source":{"id":"https://openalex.org/S30163770","display_name":"Journal of Information & Knowledge Management","issn_l":"0219-6492","issn":["0219-6492","1793-6926"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Information &amp; Knowledge Management","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034298611","display_name":"Jamuna S. Murthy","orcid":"https://orcid.org/0000-0002-9114-0441"},"institutions":[{"id":"https://openalex.org/I196608512","display_name":"PES University","ror":"https://ror.org/05m169e78","country_code":"IN","type":"education","lineage":["https://openalex.org/I196608512"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jamuna S. Murthy","raw_affiliation_strings":["PES University, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"PES University, India","institution_ids":["https://openalex.org/I196608512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056602415","display_name":"G. M. Siddesh","orcid":null},"institutions":[{"id":"https://openalex.org/I302410947","display_name":"M S Ramaiah University of Applied Sciences","ror":"https://ror.org/02anh8x74","country_code":"IN","type":"education","lineage":["https://openalex.org/I302410947"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"G. M. Siddesh","raw_affiliation_strings":["Ramaiah Institute of Technology, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ramaiah Institute of Technology, India","institution_ids":["https://openalex.org/I302410947"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110533933","display_name":"K. G. Srinivasa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094717","display_name":"National Institute of Technical Teachers Training and Research","ror":"https://ror.org/00rpc7w94","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210094717"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. G. Srinivasa","raw_affiliation_strings":["National Institute of Technical Teachers Training and Research, Chandigarh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technical Teachers Training and Research, Chandigarh, India","institution_ids":["https://openalex.org/I4210094717"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4338,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.71388644,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"18","issue":"02","first_page":"1950013","last_page":"1950013"},"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/T11644","display_name":"Spam and Phishing Detection","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9679999947547913,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.8566246032714844},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8182833194732666},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6931924819946289},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6481562852859497},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5626134872436523},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.5198757648468018},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.44884902238845825},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4351048469543457},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.43068158626556396},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4258199632167816},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3796824812889099},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.25287219882011414},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.0733751654624939}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.8566246032714844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8182833194732666},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6931924819946289},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6481562852859497},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5626134872436523},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.5198757648468018},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.44884902238845825},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4351048469543457},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.43068158626556396},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4258199632167816},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3796824812889099},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25287219882011414},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0733751654624939},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C1491633281","wikidata":"https://www.wikidata.org/wiki/Q7868","display_name":"Cell","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1142/s0219649219500138","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219649219500138","pdf_url":null,"source":{"id":"https://openalex.org/S30163770","display_name":"Journal of Information & Knowledge Management","issn_l":"0219-6492","issn":["0219-6492","1793-6926"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Information &amp; Knowledge Management","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:wsi:jikmxx:v:18:y:2019:i:02:n:s0219649219500138","is_oa":false,"landing_page_url":"http://www.worldscientific.com/doi/abs/10.1142/S0219649219500138","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1554540371","https://openalex.org/W1581659598","https://openalex.org/W1984099576","https://openalex.org/W2027321025","https://openalex.org/W2062913298","https://openalex.org/W2079281079","https://openalex.org/W2123661878","https://openalex.org/W2153635508","https://openalex.org/W2292978603","https://openalex.org/W2476111558","https://openalex.org/W2618843390","https://openalex.org/W2739463706"],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W2941935829","https://openalex.org/W3089396779","https://openalex.org/W2354902965","https://openalex.org/W2596247554","https://openalex.org/W4301373556","https://openalex.org/W3013279174","https://openalex.org/W3132372214","https://openalex.org/W2400337198","https://openalex.org/W1984947604"],"abstract_inverted_index":{"Twitter":[0],"is":[1,53,97],"considered":[2],"as":[3,79,126],"one":[4],"of":[5,112],"the":[6,72,76,115],"world\u2019s":[7],"largest":[8],"social":[9],"networking":[10],"sites":[11],"which":[12,63,84],"allow":[13],"users":[14],"to":[15,55,131],"customize":[16],"their":[17],"public":[18],"profile,":[19],"connect":[20],"with":[21,25,138],"others":[22],"and":[23,38,67,91,103,134],"interact":[24],"connected":[26],"users.":[27],"The":[28,51,95],"proposed":[29],"work":[30],"introduces":[31],"a":[32],"distributed":[33],"real-time":[34],"twitter":[35,46],"sentiment":[36,47,74],"analysis":[37,48],"visualization":[39],"framework":[40,52,116],"by":[41],"implementing":[42],"novel":[43],"algorithms":[44],"for":[45],"called":[49,61],"Emotion-Polarity-SentiWordNet.":[50],"applied":[54],"build":[56],"an":[57],"interactive":[58],"web":[59,124],"application":[60],"\u201cTwitSenti\u201d":[62],"can":[64,135],"benefit":[65],"companies":[66],"other":[68],"organizations":[69],"in":[70,85,88],"knowing":[71],"people\u2019s":[73],"towards":[75],"aspects":[77],"such":[78],"brands,":[80],"current":[81],"events,":[82],"etc.,":[83],"turn":[86],"helps":[87],"quick":[89],"decision-making":[90],"planning":[92],"marketing":[93],"strategies.":[94],"algorithm":[96],"validated":[98],"against":[99],"three":[100],"existing":[101],"classifiers":[102],"hence":[104],"proved":[105],"that":[106],"Emotion-Polarity-SentiWordNet":[107],"provides":[108],"highest":[109],"accuracy":[110],"value":[111],"85%.":[113],"Also,":[114],"showed":[117],"best":[118],"scalability":[119],"results":[120],"when":[121],"evaluated":[122],"through":[123],"app":[125],"four":[127],"node":[128],"clusters,":[129],"proves":[130],"be":[132],"fast":[133],"scale":[136],"well":[137],"massive":[139],"data.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
