{"id":"https://openalex.org/W4200581594","doi":"https://doi.org/10.1109/itnac53136.2021.9652148","title":"A Framework for Real-time Sentiment Analysis of Big Data Generated by Social Media Platforms","display_name":"A Framework for Real-time Sentiment Analysis of Big Data Generated by Social Media Platforms","publication_year":2021,"publication_date":"2021-11-24","ids":{"openalex":"https://openalex.org/W4200581594","doi":"https://doi.org/10.1109/itnac53136.2021.9652148"},"language":"en","primary_location":{"id":"doi:10.1109/itnac53136.2021.9652148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itnac53136.2021.9652148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 31st International Telecommunication Networks and Applications Conference (ITNAC)","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/A5001876507","display_name":"Kiran Fahd","orcid":"https://orcid.org/0009-0002-8213-3984"},"institutions":[{"id":"https://openalex.org/I71270174","display_name":"Victoria University","ror":"https://ror.org/04j757h98","country_code":"AU","type":"education","lineage":["https://openalex.org/I71270174"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Kiran Fahd","raw_affiliation_strings":["College of Engineering and Science Victoria University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"College of Engineering and Science Victoria University, Melbourne, Australia","institution_ids":["https://openalex.org/I71270174"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024926465","display_name":"Sazia Parvin","orcid":"https://orcid.org/0000-0001-8597-4450"},"institutions":[{"id":"https://openalex.org/I4403386716","display_name":"Melbourne Polytechnic","ror":"https://ror.org/04cq7wg91","country_code":null,"type":"education","lineage":["https://openalex.org/I4403386716"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sazia Parvin","raw_affiliation_strings":["Business & Construction Melbourne Polytechnic, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Business & Construction Melbourne Polytechnic, Melbourne, Australia","institution_ids":["https://openalex.org/I4403386716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112837997","display_name":"Anthony de Souza-Daw","orcid":null},"institutions":[{"id":"https://openalex.org/I4403386716","display_name":"Melbourne Polytechnic","ror":"https://ror.org/04cq7wg91","country_code":null,"type":"education","lineage":["https://openalex.org/I4403386716"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Anthony de Souza-Daw","raw_affiliation_strings":["Business & Construction Melbourne Polytechnic, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Business & Construction Melbourne Polytechnic, Melbourne, Australia","institution_ids":["https://openalex.org/I4403386716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5001876507"],"corresponding_institution_ids":["https://openalex.org/I71270174"],"apc_list":null,"apc_paid":null,"fwci":0.6798,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76600151,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"30","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9993000030517578,"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":0.9993000030517578,"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":0.996399998664856,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9962000250816345,"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/computer-science","display_name":"Computer science","score":0.8388582468032837},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7733054757118225},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.7633445858955383},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.7585607171058655},{"id":"https://openalex.org/keywords/spark","display_name":"SPARK (programming language)","score":0.6277384161949158},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5079415440559387},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.47581011056900024},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46214210987091064},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.45410048961639404},{"id":"https://openalex.org/keywords/unstructured-data","display_name":"Unstructured data","score":0.44485563039779663},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4150680899620056},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.319477915763855},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2940073013305664},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18937700986862183}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8388582468032837},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7733054757118225},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7633445858955383},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.7585607171058655},{"id":"https://openalex.org/C2781215313","wikidata":"https://www.wikidata.org/wiki/Q3493345","display_name":"SPARK (programming language)","level":2,"score":0.6277384161949158},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5079415440559387},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.47581011056900024},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46214210987091064},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.45410048961639404},{"id":"https://openalex.org/C2781252014","wikidata":"https://www.wikidata.org/wiki/Q1141900","display_name":"Unstructured data","level":3,"score":0.44485563039779663},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4150680899620056},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.319477915763855},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2940073013305664},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18937700986862183},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itnac53136.2021.9652148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itnac53136.2021.9652148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 31st International Telecommunication Networks and Applications Conference (ITNAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1515300461","https://openalex.org/W1528769038","https://openalex.org/W2013993544","https://openalex.org/W2031998113","https://openalex.org/W2069539533","https://openalex.org/W2145139979","https://openalex.org/W2156677278","https://openalex.org/W2165571577","https://openalex.org/W2276862765","https://openalex.org/W2323681433","https://openalex.org/W2596622777","https://openalex.org/W2735103703","https://openalex.org/W2806948703","https://openalex.org/W2911964244","https://openalex.org/W2951042832","https://openalex.org/W2954371498","https://openalex.org/W3149694855","https://openalex.org/W4205184193","https://openalex.org/W6684191474"],"related_works":["https://openalex.org/W2888662092","https://openalex.org/W3205826705","https://openalex.org/W2903394456","https://openalex.org/W2902285665","https://openalex.org/W2150818832","https://openalex.org/W2975174210","https://openalex.org/W2244029015","https://openalex.org/W2287843335","https://openalex.org/W3191926225","https://openalex.org/W2433688893"],"abstract_inverted_index":{"Sentiment":[0],"and":[1,47,70,117,131,144],"Opinion":[2],"analysis":[3,118],"have":[4,55],"been":[5,35,56],"of":[6,12,38,63,153],"significant":[7],"interest":[8],"with":[9,112],"the":[10,126,134,140,148,154],"possibilities":[11],"creating":[13,26],"more":[14],"meaningful":[15],"business":[16],"analytics":[17],"from":[18,73,90],"using":[19,30,68,99],"data":[20,71],"sources":[21,89],"such":[22,64],"as":[23,51],"social":[24,44,74,91],"media":[25,45,75,92,109],"a":[27,36,60,65,79,83,106,113],"large-scale":[28],"implementation":[29,62],"Big":[31,101],"Data.":[32],"There":[33,77],"has":[34],"range":[37],"implementation,":[39],"typically":[40],"focusing":[41],"on":[42,160],"one":[43],"platform":[46],"user":[48],"entered":[49],"text":[50],"input.":[52],"Recently,":[53],"efforts":[54],"made":[57],"to":[58,81,104],"make":[59],"real-time":[61,107],"sentiment":[66,115],"system":[67,84],"API":[69],"streams":[72],"platforms.":[76],"exists":[78],"need":[80],"create":[82],"that":[85],"uses":[86,122],"multiple":[87],"input":[88,110],"in":[93],"real-time.":[94],"We":[95],"present":[96],"an":[97],"architecture":[98],"existing":[100],"Data":[102],"technologies":[103],"implement":[105],"multi-social":[108],"source":[111],"central":[114],"extraction":[116],"component.":[119],"The":[120,151],"proposal":[121],"Apache":[123],"Kafka":[124],"for":[125,133,139,147],"ingestion":[127],"layer,":[128,136],"lexicon-based":[129],"classifier":[130],"Spark":[132],"analytical":[135],"YARN":[137],"clusters":[138],"tasks":[141],"execution":[142],"management,":[143],"MongoDB":[145],"database":[146],"storage":[149],"layer.":[150],"performance":[152],"proposed":[155],"framework":[156],"is":[157],"measured":[158],"based":[159],"different":[161],"quality":[162],"metrics.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
