{"id":"https://openalex.org/W2934012051","doi":"https://doi.org/10.1109/acit.2018.8672697","title":"The Effects of Natural Language Processing on Big Data Analysis: Sentiment Analysis Case Study","display_name":"The Effects of Natural Language Processing on Big Data Analysis: Sentiment Analysis Case Study","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2934012051","doi":"https://doi.org/10.1109/acit.2018.8672697","mag":"2934012051"},"language":"en","primary_location":{"id":"doi:10.1109/acit.2018.8672697","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit.2018.8672697","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Arab Conference on Information Technology (ACIT)","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/A5058590124","display_name":"Mariam Khader","orcid":null},"institutions":[{"id":"https://openalex.org/I158749337","display_name":"Princess Sumaya University for Technology","ror":"https://ror.org/01jy46q10","country_code":"JO","type":"education","lineage":["https://openalex.org/I158749337"]}],"countries":["JO"],"is_corresponding":false,"raw_author_name":"Mariam Khader","raw_affiliation_strings":["Computer Science, Princess Sumaya University for Technology, Amman, Jordan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science, Princess Sumaya University for Technology, Amman, Jordan","institution_ids":["https://openalex.org/I158749337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062695565","display_name":"Arafat Awajan","orcid":"https://orcid.org/0000-0002-7067-5658"},"institutions":[{"id":"https://openalex.org/I158749337","display_name":"Princess Sumaya University for Technology","ror":"https://ror.org/01jy46q10","country_code":"JO","type":"education","lineage":["https://openalex.org/I158749337"]}],"countries":["JO"],"is_corresponding":false,"raw_author_name":"Arafat Awajan","raw_affiliation_strings":["Computer Science, Princess Sumaya University for Technology, Amman, Jordan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science, Princess Sumaya University for Technology, Amman, Jordan","institution_ids":["https://openalex.org/I158749337"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004537635","display_name":"Ghazi Al\u2010Naymat","orcid":"https://orcid.org/0000-0002-9661-5354"},"institutions":[{"id":"https://openalex.org/I158749337","display_name":"Princess Sumaya University for Technology","ror":"https://ror.org/01jy46q10","country_code":"JO","type":"education","lineage":["https://openalex.org/I158749337"]}],"countries":["JO"],"is_corresponding":false,"raw_author_name":"Ghazi Al-Naymat","raw_affiliation_strings":["Computer Science, Princess Sumaya University for Technology, Amman, Jordan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science, Princess Sumaya University for Technology, Amman, Jordan","institution_ids":["https://openalex.org/I158749337"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6896,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.88583524,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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":0.9983000159263611,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.8697246313095093},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8443961143493652},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6935949325561523},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6913949847221375},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6290748119354248},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.6238099932670593},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6178234219551086},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5830111503601074},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5432454943656921},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5130883455276489},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5089278221130371},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4746689796447754},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.434222549200058},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.42133116722106934},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.4162566065788269},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3551082909107208},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09372997283935547},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.08389011025428772}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.8697246313095093},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8443961143493652},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6935949325561523},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6913949847221375},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6290748119354248},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.6238099932670593},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6178234219551086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5830111503601074},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5432454943656921},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5130883455276489},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5089278221130371},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4746689796447754},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.434222549200058},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.42133116722106934},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.4162566065788269},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3551082909107208},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09372997283935547},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.08389011025428772},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acit.2018.8672697","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit.2018.8672697","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Arab Conference on Information Technology (ACIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1750239605","https://openalex.org/W1924689489","https://openalex.org/W1984099576","https://openalex.org/W2043157037","https://openalex.org/W2115639608","https://openalex.org/W2122465391","https://openalex.org/W2156741031","https://openalex.org/W2326761481","https://openalex.org/W2400032930","https://openalex.org/W2531867140","https://openalex.org/W2584060612","https://openalex.org/W2590061102","https://openalex.org/W2608581744","https://openalex.org/W2727488328","https://openalex.org/W2751196688","https://openalex.org/W2786540448","https://openalex.org/W2803179511","https://openalex.org/W2995564009","https://openalex.org/W3088107006","https://openalex.org/W3152231500","https://openalex.org/W6751810992"],"related_works":["https://openalex.org/W1984947604","https://openalex.org/W3021501837","https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904"],"abstract_inverted_index":{"The":[0,77,108,136,154,171],"social":[1],"networks":[2],"are":[3],"one":[4],"of":[5,9,17,20,29,56,63,138,150,166,177,193],"the":[6,47,64,74,111,117,133,148,163,167,175,178,197],"main":[7],"sources":[8],"big":[10,53,151],"data.":[11],"Continuously,":[12],"it":[13],"produce":[14],"huge":[15,27],"volume":[16,28],"variety":[18],"types":[19],"data":[21,30,54,72,104,134,152,199],"at":[22],"high":[23],"velocity":[24],"rates.":[25],"This":[26],"contains":[31],"valuable":[32,69],"information":[33,70],"that":[34,174],"requires":[35],"efficient":[36],"and":[37,60,121,126,187],"scalable":[38],"analysis":[39,79,98,180],"techniques":[40,129,141,157],"to":[41,67,143],"be":[42],"extracted.":[43],"Hadoop/MapReduce":[44],"is":[45,73,106,142,181],"considered":[46],"most":[48],"suitable":[49],"framework":[50],"for":[51,100,115],"handling":[52],"because":[55],"its":[57],"scalability,":[58],"reliability":[59],"simplicity.":[61],"One":[62],"basic":[65],"applications":[66],"extract":[68],"from":[71],"sentiment":[75,78,97,179],"analysis.":[76],"studies":[80],"peoples'":[81],"opinion":[82],"by":[83,183],"classifying":[84,116],"their":[85,145],"written":[86],"text":[87,118],"into":[88,119],"positive":[89,120],"or":[90],"negative":[91,122],"polarity.":[92,123],"In":[93],"this":[94],"work,":[95],"a":[96,102],"method":[99,109],"analyzing":[101],"Twitter":[103],"set":[105],"analyzed.":[107],"uses":[110],"Naive":[112,168],"Bayes":[113,169],"algorithm":[114],"Several":[124],"linguistic":[125,188],"NLP":[127,186],"preprocessing":[128,140,156],"were":[130],"applied":[131,155],"on":[132,147,196],"set.":[135,200],"aim":[137],"these":[139],"study":[144],"effects":[146],"quality":[149],"classification.":[153],"have":[158],"achieved":[159],"an":[160,191],"enhancement":[161],"in":[162],"classification":[164],"accuracy":[165,192],"algorithm.":[170],"experiments":[172],"prove":[173],"performance":[176],"enhanced":[182],"5%":[184],"using":[185],"processing,":[189],"yielding":[190],"73":[194],"%":[195],"used":[198]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}