{"id":"https://openalex.org/W4310253184","doi":"https://doi.org/10.17977/um018v5i12022p41-52","title":"A Comparison of Machine Learning Models to Prioritise Emailsusing Emotion Analysis for Customer Service Excellence","display_name":"A Comparison of Machine Learning Models to Prioritise Emailsusing Emotion Analysis for Customer Service Excellence","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W4310253184","doi":"https://doi.org/10.17977/um018v5i12022p41-52"},"language":"en","primary_location":{"id":"doi:10.17977/um018v5i12022p41-52","is_oa":true,"landing_page_url":"https://doi.org/10.17977/um018v5i12022p41-52","pdf_url":"http://journal2.um.ac.id/index.php/keds/article/download/29270/10680","source":{"id":"https://openalex.org/S4210237352","display_name":"Knowledge Engineering and Data Science","issn_l":"2597-4602","issn":["2597-4602","2597-4637"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310314921","host_organization_name":"State University of Malang","host_organization_lineage":["https://openalex.org/P4310314921"],"host_organization_lineage_names":["State University of Malang"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge Engineering and Data Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"http://journal2.um.ac.id/index.php/keds/article/download/29270/10680","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062736182","display_name":"Mohammad Yasser Chuttur","orcid":"https://orcid.org/0000-0002-6049-8272"},"institutions":[{"id":"https://openalex.org/I69072986","display_name":"University of Mauritius","ror":"https://ror.org/05cyprz33","country_code":"MU","type":"education","lineage":["https://openalex.org/I69072986"]}],"countries":["MU"],"is_corresponding":true,"raw_author_name":"Mohammad Yasser Chuttur","raw_affiliation_strings":["University of Mauritius"],"affiliations":[{"raw_affiliation_string":"University of Mauritius","institution_ids":["https://openalex.org/I69072986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052406269","display_name":"Yashinee Parianen","orcid":null},"institutions":[{"id":"https://openalex.org/I69072986","display_name":"University of Mauritius","ror":"https://ror.org/05cyprz33","country_code":"MU","type":"education","lineage":["https://openalex.org/I69072986"]}],"countries":["MU"],"is_corresponding":false,"raw_author_name":"Yashinee Parianen","raw_affiliation_strings":["University of Mauritius"],"affiliations":[{"raw_affiliation_string":"University of Mauritius","institution_ids":["https://openalex.org/I69072986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062736182"],"corresponding_institution_ids":["https://openalex.org/I69072986"],"apc_list":null,"apc_paid":null,"fwci":0.4577,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.67216031,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"5","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13155","display_name":"Digital Communication and Language","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T13155","display_name":"Digital Communication and Language","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.9869999885559082,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9854000210762024,"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/machine-learning","display_name":"Machine learning","score":0.8095518350601196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.761559784412384},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.652301549911499},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6325767636299133},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.5072064399719238},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.47360682487487793},{"id":"https://openalex.org/keywords/excellence","display_name":"Excellence","score":0.4469371438026428},{"id":"https://openalex.org/keywords/service","display_name":"Service (business)","score":0.4238688051700592}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.8095518350601196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.761559784412384},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.652301549911499},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6325767636299133},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.5072064399719238},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.47360682487487793},{"id":"https://openalex.org/C2777352838","wikidata":"https://www.wikidata.org/wiki/Q5419420","display_name":"Excellence","level":2,"score":0.4469371438026428},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.4238688051700592},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C136264566","wikidata":"https://www.wikidata.org/wiki/Q159810","display_name":"Economy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.17977/um018v5i12022p41-52","is_oa":true,"landing_page_url":"https://doi.org/10.17977/um018v5i12022p41-52","pdf_url":"http://journal2.um.ac.id/index.php/keds/article/download/29270/10680","source":{"id":"https://openalex.org/S4210237352","display_name":"Knowledge Engineering and Data Science","issn_l":"2597-4602","issn":["2597-4602","2597-4637"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310314921","host_organization_name":"State University of Malang","host_organization_lineage":["https://openalex.org/P4310314921"],"host_organization_lineage_names":["State University of Malang"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge Engineering and Data Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6fafa9ffea354084836bcb8d1fa3acbe","is_oa":true,"landing_page_url":"https://doaj.org/article/6fafa9ffea354084836bcb8d1fa3acbe","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Knowledge Engineering and Data Science, Vol 5, Iss 1, Pp 41-52 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.17977/um018v5i12022p41-52","is_oa":true,"landing_page_url":"https://doi.org/10.17977/um018v5i12022p41-52","pdf_url":"http://journal2.um.ac.id/index.php/keds/article/download/29270/10680","source":{"id":"https://openalex.org/S4210237352","display_name":"Knowledge Engineering and Data Science","issn_l":"2597-4602","issn":["2597-4602","2597-4637"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310314921","host_organization_name":"State University of Malang","host_organization_lineage":["https://openalex.org/P4310314921"],"host_organization_lineage_names":["State University of Malang"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge Engineering and Data Science","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5,"display_name":"No poverty","id":"https://metadata.un.org/sdg/1"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4310253184.pdf","grobid_xml":"https://content.openalex.org/works/W4310253184.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1572786359","https://openalex.org/W2106004099","https://openalex.org/W2130624643","https://openalex.org/W2184363542","https://openalex.org/W2399618090","https://openalex.org/W2419486802","https://openalex.org/W2782659463","https://openalex.org/W2783783766","https://openalex.org/W2804934982","https://openalex.org/W2805865301","https://openalex.org/W2809895060","https://openalex.org/W2889988224","https://openalex.org/W2901292257","https://openalex.org/W2910051269","https://openalex.org/W2914182082","https://openalex.org/W2949836779","https://openalex.org/W2953370657","https://openalex.org/W2975822798","https://openalex.org/W2989568949","https://openalex.org/W3000358430","https://openalex.org/W3003626604","https://openalex.org/W3005707813","https://openalex.org/W3025488764","https://openalex.org/W3040598142","https://openalex.org/W3087484287","https://openalex.org/W3091480024","https://openalex.org/W3092892846","https://openalex.org/W3109575922","https://openalex.org/W3126641643","https://openalex.org/W3131274534","https://openalex.org/W3136740017","https://openalex.org/W3156079955","https://openalex.org/W3166981948","https://openalex.org/W3185661979","https://openalex.org/W3186370456","https://openalex.org/W4205485659","https://openalex.org/W4205840321","https://openalex.org/W4210312870","https://openalex.org/W4220992348","https://openalex.org/W4232266556","https://openalex.org/W4288076027","https://openalex.org/W4293239361","https://openalex.org/W4295837454","https://openalex.org/W6634202635","https://openalex.org/W6773296534","https://openalex.org/W6806096950"],"related_works":["https://openalex.org/W2140536630","https://openalex.org/W2391730868","https://openalex.org/W2154960005","https://openalex.org/W2759814045","https://openalex.org/W2118055728","https://openalex.org/W3012393071","https://openalex.org/W2736760277","https://openalex.org/W4386940087","https://openalex.org/W4386931226","https://openalex.org/W3125583970"],"abstract_inverted_index":{"There":[0],"has":[1],"been":[2],"little":[3],"research":[4],"on":[5,43,121,139,181],"machine":[6,27,104,130,192],"learning":[7,28,105,131,193],"for":[8,11,30,93,198],"email":[9,49,88,199],"prioritization":[10],"customer":[12,76],"service":[13],"excellence.":[14],"To":[15],"fill":[16],"this":[17],"gap,":[18],"we":[19,98,152],"propose":[20],"and":[21,40,73,100,110,112,118,158],"assess":[22],"the":[23,44,48,80,122,149,156,162,170,174,183],"efficacy":[24],"of":[25,36,90,115,167],"various":[26],"techniques":[29],"classifying":[31],"emails":[32,56,70,137],"into":[33,59],"three":[34,61],"degrees":[35],"priority:":[37],"high,":[38],"low,":[39],"neutral,":[41],"based":[42,138],"emotions":[45,197],"inherent":[46],"in":[47],"content.":[50,142],"It":[51],"is":[52],"predicted":[53],"that":[54,129,155,191,195,205],"after":[55],"are":[57,201],"classified":[58],"those":[60],"categories,":[62],"recipients":[63],"will":[64],"be":[65,133,207],"able":[66],"to":[67,69,84,135],"respond":[68],"more":[71],"efficiently":[72],"provide":[74],"better":[75],"service.":[77],"We":[78,189],"use":[79],"NRC":[81],"Emotion":[82],"Lexicon":[83],"construct":[85],"a":[86,202],"labeled":[87,123],"dataset":[89,184],"517,401":[91],"messages":[92],"our":[94],"proposal.":[95],"Following":[96],"that,":[97],"train":[99],"test":[101],"four":[102],"prominent":[103],"models,":[106],"MNB,":[107,116],"SVM,":[108],"LogR,":[109],"RF,":[111],"an":[113,165],"Ensemble":[114],"LSVC,":[117],"RF":[119],"classifiers,":[120],"dataset.":[124],"Our":[125],"main":[126],"findings":[127],"suggest":[128],"may":[132],"used":[134],"classify":[136],"their":[140],"emotional":[141],"However,":[143],"some":[144],"models":[145,160,194],"outperform":[146],"others.":[147],"During":[148],"testing":[150],"phase,":[151],"also":[153],"discovered":[154],"LogR":[157],"LSVC":[159],"performed":[161,173],"best,":[163],"with":[164],"accuracy":[166],"72%,":[168],"while":[169],"MNB":[171],"classifier":[172],"poorest.":[175],"Furthermore,":[176],"classification":[177,200],"performance":[178],"differed":[179],"depending":[180],"whether":[182],"was":[185],"balanced":[186],"or":[187],"imbalanced.":[188],"conclude":[190],"employ":[196],"promising":[203],"avenue":[204],"should":[206],"explored":[208],"further.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}