{"id":"https://openalex.org/W3097820232","doi":"https://doi.org/10.1093/comjnl/bxaa114","title":"Redis-Based Messaging Queue and Cache-Enabled Parallel Processing Social Media Analytics Framework","display_name":"Redis-Based Messaging Queue and Cache-Enabled Parallel Processing Social Media Analytics Framework","publication_year":2020,"publication_date":"2020-08-11","ids":{"openalex":"https://openalex.org/W3097820232","doi":"https://doi.org/10.1093/comjnl/bxaa114","mag":"3097820232"},"language":"en","primary_location":{"id":"doi:10.1093/comjnl/bxaa114","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxaa114","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","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/A5044411063","display_name":"Ravindra Kumar Singh","orcid":"https://orcid.org/0000-0003-1142-1954"},"institutions":[{"id":"https://openalex.org/I70971781","display_name":"Dr. B. R. Ambedkar National Institute of Technology Jalandhar","ror":"https://ror.org/03xt0bg88","country_code":"IN","type":"education","lineage":["https://openalex.org/I70971781"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Ravindra Kumar Singh","raw_affiliation_strings":["Department of Computer Science and Engineering, Dr. B. R. Ambedkar National Institute of Technology, G.T. Road, Amritsar Bye-Pass, Jalandhar (Punjab), India. Zip Code- 144011"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Dr. B. R. Ambedkar National Institute of Technology, G.T. Road, Amritsar Bye-Pass, Jalandhar (Punjab), India. Zip Code- 144011","institution_ids":["https://openalex.org/I70971781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102757544","display_name":"Harsh Kumar Verma","orcid":"https://orcid.org/0000-0003-4826-6150"},"institutions":[{"id":"https://openalex.org/I70971781","display_name":"Dr. B. R. Ambedkar National Institute of Technology Jalandhar","ror":"https://ror.org/03xt0bg88","country_code":"IN","type":"education","lineage":["https://openalex.org/I70971781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Harsh Kumar Verma","raw_affiliation_strings":["Department of Computer Science and Engineering, Dr. B. R. Ambedkar National Institute of Technology, G.T. Road, Amritsar Bye-Pass, Jalandhar (Punjab), India. Zip Code- 144011"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Dr. B. R. Ambedkar National Institute of Technology, G.T. Road, Amritsar Bye-Pass, Jalandhar (Punjab), India. Zip Code- 144011","institution_ids":["https://openalex.org/I70971781"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5044411063"],"corresponding_institution_ids":["https://openalex.org/I70971781"],"apc_list":{"value":2635,"currency":"GBP","value_usd":3232},"apc_paid":null,"fwci":1.043,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.8256778,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"65","issue":"4","first_page":"843","last_page":"857"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9976000189781189,"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":0.9976000189781189,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9937999844551086,"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"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9894999861717224,"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/computer-science","display_name":"Computer science","score":0.8812830448150635},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.6019514799118042},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6013094186782837},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5681385397911072},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.56169193983078},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5545206665992737},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.5495315194129944},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5484845638275146},{"id":"https://openalex.org/keywords/data-analysis","display_name":"Data analysis","score":0.4279100298881531},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4209875166416168},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4144873023033142},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4021582305431366},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35229969024658203},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.2722378373146057},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2344391942024231},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.14585766196250916}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8812830448150635},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.6019514799118042},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6013094186782837},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5681385397911072},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.56169193983078},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5545206665992737},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.5495315194129944},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5484845638275146},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.4279100298881531},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4209875166416168},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4144873023033142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4021582305431366},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35229969024658203},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2722378373146057},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2344391942024231},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.14585766196250916}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1093/comjnl/bxaa114","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comjnl/bxaa114","pdf_url":null,"source":{"id":"https://openalex.org/S44643521","display_name":"The Computer Journal","issn_l":"0010-4620","issn":["0010-4620","1460-2067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Computer Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2000588299","https://openalex.org/W2026202763","https://openalex.org/W2117332520","https://openalex.org/W2140291099","https://openalex.org/W2275236824","https://openalex.org/W2355918526","https://openalex.org/W2396708059","https://openalex.org/W2585577269","https://openalex.org/W2626775212","https://openalex.org/W2732264101","https://openalex.org/W2747288535","https://openalex.org/W2750351539","https://openalex.org/W2771016175","https://openalex.org/W2780195716","https://openalex.org/W2789727803","https://openalex.org/W2796460143","https://openalex.org/W2811000347","https://openalex.org/W2883564063","https://openalex.org/W2888421737","https://openalex.org/W2889771151","https://openalex.org/W2893591486","https://openalex.org/W2894023585","https://openalex.org/W2904344771","https://openalex.org/W2906688264","https://openalex.org/W2941443247","https://openalex.org/W2951706634","https://openalex.org/W3021678642","https://openalex.org/W4236908389","https://openalex.org/W6740181858","https://openalex.org/W6756939699","https://openalex.org/W6776890396"],"related_works":["https://openalex.org/W4226266853","https://openalex.org/W4210252074","https://openalex.org/W3092201768","https://openalex.org/W2796632413","https://openalex.org/W2740083192","https://openalex.org/W4382315681","https://openalex.org/W2794907032","https://openalex.org/W4255802207","https://openalex.org/W3123352720","https://openalex.org/W2462007151"],"abstract_inverted_index":{"Abstract":[0],"The":[1,80],"extensive":[2],"usage":[3],"of":[4,25,46,58,82,126,128,138,161],"social":[5],"media":[6],"polarity":[7],"analysis":[8,115,180],"claims":[9,121],"the":[10,26,89,120,124,136,151,188],"need":[11],"for":[12,178],"real-time":[13,109],"analytics":[14,106],"and":[15,32,35,66,73,99,110,122,142,170,184],"runtime":[16],"outcomes":[17],"on":[18,116,181],"dashboards.":[19],"In":[20],"data":[21,40,65,70,105,129],"analytics,":[22],"only":[23],"30%":[24],"time":[27,76],"is":[28,37,86],"consumed":[29,38],"in":[30,39,55,63,108,192],"modeling":[31],"evaluation":[33],"stages":[34],"70%":[36],"engineering":[41,71],"tasks.":[42],"There":[43],"are":[44],"lots":[45],"machine":[47,175],"learning":[48,176],"algorithms":[49],"to":[50,87,102,149],"achieve":[51],"a":[52,94,159],"desirable":[53],"outcome":[54],"prediction":[56,152],"points":[57],"view,":[59],"but":[60],"they":[61],"lack":[62],"handling":[64],"their":[67],"transformation":[68],"so-called":[69],"tasks,":[72],"reducing":[74],"its":[75],"remained":[77],"still":[78],"challenging.":[79],"contribution":[81],"this":[83,155,193],"research":[84,133,156],"paper":[85],"encounter":[88],"mentioned":[90,140],"challenges":[91],"by":[92],"presenting":[93],"parallelly,":[95],"scalable,":[96],"effective,":[97],"responsive":[98],"fault-tolerant":[100],"framework":[101],"perform":[103],"end-to-end":[104],"tasks":[107],"batch-processing":[111],"manner.":[112],"An":[113],"experimental":[114],"Twitter":[117,182],"posts":[118,183],"supported":[119],"signifies":[123],"benefits":[125],"parallelism":[127],"processing":[130,139],"units.":[131],"This":[132],"has":[134],"highlighted":[135],"importance":[137],"URLs":[141],"embedded":[143],"images":[144],"along":[145],"with":[146],"post":[147],"content":[148],"boost":[150],"efficiency.":[153],"Furthermore,":[154],"additionally":[157],"provided":[158],"comparison":[160],"naive":[162],"Bayes,":[163],"support":[164],"vector":[165],"machines,":[166],"extreme":[167],"gradient":[168],"boosting":[169],"long":[171],"short-term":[172],"memory":[173],"(LSTM)":[174],"techniques":[177],"sentiment":[179],"concluded":[185],"LSTM":[186],"as":[187],"most":[189],"effective":[190],"technique":[191],"regard.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
