{"id":"https://openalex.org/W3005571537","doi":"https://doi.org/10.1109/wocn45266.2019.8995109","title":"A BigData approach for sentiment analysis of twitter data using Naive Bayes and SVM Algorithm","display_name":"A BigData approach for sentiment analysis of twitter data using Naive Bayes and SVM Algorithm","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3005571537","doi":"https://doi.org/10.1109/wocn45266.2019.8995109","mag":"3005571537"},"language":"en","primary_location":{"id":"doi:10.1109/wocn45266.2019.8995109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wocn45266.2019.8995109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Sixteenth International Conference on Wireless and Optical Communication Networks (WOCN)","raw_type":"proceedings-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/A5057480829","display_name":"Priyanshu Jadon","orcid":null},"institutions":[{"id":"https://openalex.org/I4210115061","display_name":"Sri Aurobindo Institute of Technology","ror":"https://ror.org/028s4s402","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210115061"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Priyanshu Jadon","raw_affiliation_strings":["Sri Aurobindo Institute of Technology, Indore"],"affiliations":[{"raw_affiliation_string":"Sri Aurobindo Institute of Technology, Indore","institution_ids":["https://openalex.org/I4210115061"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065461385","display_name":"Deepshikha Bhatia","orcid":"https://orcid.org/0000-0003-1203-1069"},"institutions":[{"id":"https://openalex.org/I4210154633","display_name":"Inspiration Innovation Synergy University","ror":"https://ror.org/04d3d5q14","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210154633"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Deepshikha Bhatia","raw_affiliation_strings":["The IIS University, Jaipur"],"affiliations":[{"raw_affiliation_string":"The IIS University, Jaipur","institution_ids":["https://openalex.org/I4210154633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107841507","display_name":"Durgesh Kumar Mishra","orcid":null},"institutions":[{"id":"https://openalex.org/I4210115061","display_name":"Sri Aurobindo Institute of Technology","ror":"https://ror.org/028s4s402","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210115061"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Durgesh Kumar Mishra","raw_affiliation_strings":["Sri Aurobindo institute of Technology"],"affiliations":[{"raw_affiliation_string":"Sri Aurobindo institute of Technology","institution_ids":["https://openalex.org/I4210115061"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057480829"],"corresponding_institution_ids":["https://openalex.org/I4210115061"],"apc_list":null,"apc_paid":null,"fwci":0.5781,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.77073816,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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":0.9998999834060669,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9783999919891357,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.9086830615997314},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.8164618015289307},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.799222469329834},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.7021390795707703},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6883252263069153},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.6398151516914368},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5268805623054504},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5153774619102478},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5033196806907654},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.49492329359054565},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4004471004009247},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3234652280807495},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2789732813835144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27555614709854126}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.9086830615997314},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.8164618015289307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.799222469329834},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.7021390795707703},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6883252263069153},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.6398151516914368},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5268805623054504},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5153774619102478},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5033196806907654},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.49492329359054565},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4004471004009247},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3234652280807495},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2789732813835144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27555614709854126},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wocn45266.2019.8995109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wocn45266.2019.8995109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Sixteenth International Conference on Wireless and Optical Communication Networks (WOCN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2019759670","https://openalex.org/W2126581182","https://openalex.org/W2148122886","https://openalex.org/W2149167588","https://openalex.org/W2296734373","https://openalex.org/W2319344758","https://openalex.org/W2606271988","https://openalex.org/W2735103703","https://openalex.org/W2740210342","https://openalex.org/W2949998441","https://openalex.org/W4236192045","https://openalex.org/W4236345704","https://openalex.org/W6678923525","https://openalex.org/W6697591862","https://openalex.org/W6764146914","https://openalex.org/W6817578933"],"related_works":["https://openalex.org/W2385368906","https://openalex.org/W2902924992","https://openalex.org/W2626642044","https://openalex.org/W93537448","https://openalex.org/W2619807045","https://openalex.org/W2388758053","https://openalex.org/W2949734191","https://openalex.org/W2017333877","https://openalex.org/W2048332520","https://openalex.org/W3021501837"],"abstract_inverted_index":{"Data":[0],"mining":[1],"and":[2,32,37,51,75,101,133,147],"sentiment":[3,141,156],"analysis":[4,22,79,106,142,157],"are":[5],"two":[6],"most":[7],"versatile":[8],"research":[9],"areas":[10],"in":[11],"field":[12],"of":[13,35,54,65,87,103,107,117,130,151],"real":[14],"time":[15,19],"knowledge":[16],"extraction.":[17],"Real":[18],"twitter":[20,108],"data":[21,57],"can":[23,58,68,110,124],"plays":[24],"very":[25],"crucial":[26],"role":[27],"to":[28,47,62,71,83,97,112,126,144,168],"observe":[29,63,145],"the":[30,81],"thinking":[31,135],"view":[33,115,122,149],"point":[34,116,123,150],"people":[36],"users.":[38],"Nowadays,":[39],"social":[40,55],"networking":[41,56],"sites":[42],"have":[43],"become":[44],"centric":[45],"points":[46],"share":[48],"your":[49],"thoughts":[50],"viewpoints.":[52],"Analysis":[53],"help":[59,70,96,111,125],"a":[60],"lot":[61],"trend":[64],"society.":[66],"It":[67,94],"also":[69,95],"derive":[72,98,127],"user":[73,99,109],"interest":[74],"hidden":[76],"activities.":[77],"Sentiment":[78,105],"is":[80,89],"approach":[82],"determine":[84],"whether":[85],"piece":[86],"writing":[88],"positive,":[90],"negative":[91,148],"or":[92],"neutral.":[93],"opinion":[100,129],"attitude":[102],"writer.":[104],"track":[113],"eventual":[114],"user.":[118],"Country":[119],"wise":[120],"accumulative":[121],"overall":[128],"country":[131],"citizens":[132],"their":[134],"criteria.":[136],"This":[137],"work":[138,161],"has":[139],"proposed":[140],"model":[143],"positive":[146],"different":[152],"countries":[153],"based":[154],"on":[155,172],"approach.":[158],"The":[159],"complete":[160],"will":[162],"be":[163],"implemented":[164],"using":[165],"Hadoop":[166],"Ecosystem":[167],"perform":[169],"parallel":[170],"processing":[171],"large":[173],"data.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}
