{"id":"https://openalex.org/W2972571474","doi":"https://doi.org/10.4018/ijdwm.2019100102","title":"The Application of Sentiment Analysis and Text Analytics to Customer Experience Reviews to Understand What Customers Are Really Saying","display_name":"The Application of Sentiment Analysis and Text Analytics to Customer Experience Reviews to Understand What Customers Are Really Saying","publication_year":2019,"publication_date":"2019-09-13","ids":{"openalex":"https://openalex.org/W2972571474","doi":"https://doi.org/10.4018/ijdwm.2019100102","mag":"2972571474"},"language":"en","primary_location":{"id":"doi:10.4018/ijdwm.2019100102","is_oa":true,"landing_page_url":"https://doi.org/10.4018/ijdwm.2019100102","pdf_url":"https://www.igi-global.com/ViewTitle.aspx?TitleId=237136&isxn=9781522564218","source":{"id":"https://openalex.org/S53932126","display_name":"International Journal of Data Warehousing and Mining","issn_l":"1548-3924","issn":["1548-3924","1548-3932"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Warehousing and Mining","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.igi-global.com/ViewTitle.aspx?TitleId=237136&isxn=9781522564218","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026908062","display_name":"Conor Gallagher","orcid":null},"institutions":[{"id":"https://openalex.org/I18452974","display_name":"Letterkenny Institute of Technology","ror":"https://ror.org/04ps1tq95","country_code":"IE","type":"education","lineage":["https://openalex.org/I18452974"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Conor Gallagher","raw_affiliation_strings":["Letterkenny Institute of Technology, Donegal, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Letterkenny Institute of Technology, Donegal, Ireland","institution_ids":["https://openalex.org/I18452974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059211616","display_name":"Eoghan Furey","orcid":"https://orcid.org/0000-0002-6697-1462"},"institutions":[{"id":"https://openalex.org/I18452974","display_name":"Letterkenny Institute of Technology","ror":"https://ror.org/04ps1tq95","country_code":"IE","type":"education","lineage":["https://openalex.org/I18452974"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Eoghan Furey","raw_affiliation_strings":["Letterkenny Institute of Technology, Donegal, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Letterkenny Institute of Technology, Donegal, Ireland","institution_ids":["https://openalex.org/I18452974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002868461","display_name":"Kevin Curran","orcid":"https://orcid.org/0000-0001-5237-5355"},"institutions":[{"id":"https://openalex.org/I138801177","display_name":"University of Ulster","ror":"https://ror.org/01yp9g959","country_code":"GB","type":"education","lineage":["https://openalex.org/I138801177"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kevin Curran","raw_affiliation_strings":["Ulster University, Derry, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ulster University, Derry, UK","institution_ids":["https://openalex.org/I138801177"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7475,"has_fulltext":true,"cited_by_count":49,"citation_normalized_percentile":{"value":0.92616103,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"15","issue":"4","first_page":"21","last_page":"47"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9986000061035156,"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":0.9986000061035156,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.995199978351593,"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/T10609","display_name":"Digital Marketing and Social Media","score":0.9797999858856201,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.8016440868377686},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6732333898544312},{"id":"https://openalex.org/keywords/customer-intelligence","display_name":"Customer intelligence","score":0.6495156288146973},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5863706469535828},{"id":"https://openalex.org/keywords/customer-retention","display_name":"Customer retention","score":0.5584840774536133},{"id":"https://openalex.org/keywords/customer-satisfaction","display_name":"Customer satisfaction","score":0.5239731669425964},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5140870213508606},{"id":"https://openalex.org/keywords/unstructured-data","display_name":"Unstructured data","score":0.5096957683563232},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.48541387915611267},{"id":"https://openalex.org/keywords/loyalty","display_name":"Loyalty","score":0.47976645827293396},{"id":"https://openalex.org/keywords/loyalty-business-model","display_name":"Loyalty business model","score":0.4736976623535156},{"id":"https://openalex.org/keywords/customer-to-customer","display_name":"Customer to customer","score":0.46055734157562256},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.45133477449417114},{"id":"https://openalex.org/keywords/customer-relationship-management","display_name":"Customer relationship management","score":0.4180352985858917},{"id":"https://openalex.org/keywords/voice-of-the-customer","display_name":"Voice of the customer","score":0.4108772277832031},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.3412216305732727},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.32644903659820557},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.23582962155342102},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.22901752591133118},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18946629762649536},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.17662596702575684},{"id":"https://openalex.org/keywords/service","display_name":"Service (business)","score":0.13111504912376404},{"id":"https://openalex.org/keywords/service-quality","display_name":"Service quality","score":0.09252867102622986}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.8016440868377686},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6732333898544312},{"id":"https://openalex.org/C57660159","wikidata":"https://www.wikidata.org/wiki/Q5196460","display_name":"Customer intelligence","level":5,"score":0.6495156288146973},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5863706469535828},{"id":"https://openalex.org/C101276457","wikidata":"https://www.wikidata.org/wiki/Q5196474","display_name":"Customer retention","level":4,"score":0.5584840774536133},{"id":"https://openalex.org/C191511416","wikidata":"https://www.wikidata.org/wiki/Q999278","display_name":"Customer satisfaction","level":2,"score":0.5239731669425964},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5140870213508606},{"id":"https://openalex.org/C2781252014","wikidata":"https://www.wikidata.org/wiki/Q1141900","display_name":"Unstructured data","level":3,"score":0.5096957683563232},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.48541387915611267},{"id":"https://openalex.org/C2776967331","wikidata":"https://www.wikidata.org/wiki/Q1132131","display_name":"Loyalty","level":2,"score":0.47976645827293396},{"id":"https://openalex.org/C146897074","wikidata":"https://www.wikidata.org/wiki/Q1932925","display_name":"Loyalty business model","level":4,"score":0.4736976623535156},{"id":"https://openalex.org/C63207073","wikidata":"https://www.wikidata.org/wiki/Q1076010","display_name":"Customer to customer","level":5,"score":0.46055734157562256},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.45133477449417114},{"id":"https://openalex.org/C98825075","wikidata":"https://www.wikidata.org/wiki/Q485643","display_name":"Customer relationship management","level":2,"score":0.4180352985858917},{"id":"https://openalex.org/C43595421","wikidata":"https://www.wikidata.org/wiki/Q7939596","display_name":"Voice of the customer","level":5,"score":0.4108772277832031},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.3412216305732727},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.32644903659820557},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.23582962155342102},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.22901752591133118},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18946629762649536},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.17662596702575684},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.13111504912376404},{"id":"https://openalex.org/C140781008","wikidata":"https://www.wikidata.org/wiki/Q1221081","display_name":"Service quality","level":3,"score":0.09252867102622986},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.4018/ijdwm.2019100102","is_oa":true,"landing_page_url":"https://doi.org/10.4018/ijdwm.2019100102","pdf_url":"https://www.igi-global.com/ViewTitle.aspx?TitleId=237136&isxn=9781522564218","source":{"id":"https://openalex.org/S53932126","display_name":"International Journal of Data Warehousing and Mining","issn_l":"1548-3924","issn":["1548-3924","1548-3932"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Warehousing and Mining","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/37cc28f2-4b50-430c-a552-63597c95534c","is_oa":true,"landing_page_url":"https://pure.ulster.ac.uk/en/publications/37cc28f2-4b50-430c-a552-63597c95534c","pdf_url":"https://pure.ulster.ac.uk/en/publications/37cc28f2-4b50-430c-a552-63597c95534c","source":{"id":"https://openalex.org/S4306402454","display_name":"Ulster University Research Portal (Ulster University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138801177","host_organization_name":"University of Ulster","host_organization_lineage":["https://openalex.org/I138801177"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Gallagher, C, Furey, E & Curran, K 2019, 'The Application of Sentiment Analysis and Text Analytics to Customer Experience Reviews to Understand What Customers Are Really Saying', International Journal of Data Warehousing and Mining (IJDWM), vol. 15, no. 4, 2, pp. 21-47. https://doi.org/10.4018/IJDWM.2019100102","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:RePEc:igg:jdwm00:v:15:y:2019:i:4:p:21-47","is_oa":false,"landing_page_url":"https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJDWM.2019100102","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.4018/ijdwm.2019100102","is_oa":true,"landing_page_url":"https://doi.org/10.4018/ijdwm.2019100102","pdf_url":"https://www.igi-global.com/ViewTitle.aspx?TitleId=237136&isxn=9781522564218","source":{"id":"https://openalex.org/S53932126","display_name":"International Journal of Data Warehousing and Mining","issn_l":"1548-3924","issn":["1548-3924","1548-3932"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Warehousing and Mining","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2972571474.pdf","grobid_xml":"https://content.openalex.org/works/W2972571474.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W75464833","https://openalex.org/W1499516075","https://openalex.org/W1514707997","https://openalex.org/W1606653819","https://openalex.org/W1975428268","https://openalex.org/W1984725670","https://openalex.org/W2009657717","https://openalex.org/W2011799606","https://openalex.org/W2019759670","https://openalex.org/W2031213082","https://openalex.org/W2037163971","https://openalex.org/W2039796390","https://openalex.org/W2120708938","https://openalex.org/W2125800352","https://openalex.org/W2132314509","https://openalex.org/W2132709258","https://openalex.org/W2135768893","https://openalex.org/W2141631351","https://openalex.org/W2141975087","https://openalex.org/W2143455647","https://openalex.org/W2146096861","https://openalex.org/W2151790155","https://openalex.org/W2165740683","https://openalex.org/W2250456019","https://openalex.org/W2251075512","https://openalex.org/W2413899610","https://openalex.org/W2735364069","https://openalex.org/W2835346836","https://openalex.org/W3215638535","https://openalex.org/W4229800626"],"related_works":["https://openalex.org/W2130694230","https://openalex.org/W3013184534","https://openalex.org/W2483231811","https://openalex.org/W2499260457","https://openalex.org/W2181766440","https://openalex.org/W2124748206","https://openalex.org/W4284957919","https://openalex.org/W4284958903","https://openalex.org/W2422895071","https://openalex.org/W2372647104"],"abstract_inverted_index":{"In":[0],"a":[1,12,39,47,78,88,111,187,190,204,208,246,252,257,266,292,300],"world":[2],"of":[3,15,46,87,99,119,144,153,164,192,210,259,277,281],"ever-growing":[4],"customer":[5,49,74,80,130,139,262,271,296],"data,":[6],"businesses":[7],"are":[8,103],"required":[9],"to":[10,59,69,76,92,128,160,176,183,194,207,230],"have":[11],"clear":[13],"line":[14],"sight":[16],"into":[17,34],"what":[18,101,168],"their":[19,62,73,278,295],"customers":[20,102,166],"think":[21,171],"about":[22,105],"the":[23,44,85,97,120,135,142,151,162,174,201,231,237,270,275,282],"business,":[24],"its":[25],"products,":[26,106],"people":[27],"and":[28,52,57,71,108,124,147,213,235,274],"how":[29,184],"it":[30,125,216,229,288],"treats":[31],"them.":[32],"Insight":[33],"these":[35],"critical":[36],"areas":[37],"for":[38,67],"business":[40,68,239,247,293],"will":[41],"aid":[42,93],"in":[43,53,96,141,150],"development":[45],"robust":[48,301],"experience":[50],"strategy":[51],"turn":[54],"drive":[55,77],"loyalty":[56],"recommendations":[58],"others":[60],"by":[61],"customers.":[63],"It":[64],"is":[65,114,126,265,289],"key":[66,127],"access":[70],"mine":[72],"data":[75,123,149],"modern":[79],"experience.":[81,263],"This":[82,113],"article":[83],"investigates":[84],"use":[86],"text":[89,179],"mining":[90],"approach":[91],"sentiment":[94,140,205,225,276,302],"analysis":[95,303],"pursuit":[98],"understanding":[100],"saying":[104],"services":[107],"interactions":[109],"with":[110,299],"business.":[112],"commonly":[115],"known":[116],"as":[117,181,217,256],"Voice":[118],"Customer":[121],"(VOC)":[122],"unlocking":[129],"sentiment.":[131],"The":[132,241,284],"authors":[133,202,285],"analyse":[134],"relationship":[136],"between":[137,269],"unstructured":[138],"form":[143,152],"verbatim":[145,211],"feedback":[146,180,212,297],"structured":[148],"user":[154],"review":[155,280],"ratings":[156,159,272],"or":[157,220],"satisfaction":[158],"explore":[161],"question":[163],"whether":[165],"say":[167],"they":[169,185,227],"really":[170],"when":[172],"given":[173],"opportunity":[175],"provide":[177],"free":[178],"opposed":[182],"rate":[186],"product":[188],"on":[189,251],"scale":[191],"one":[193],"five.":[195],"Using":[196,222],"various":[197],"Sentiment":[198],"Analysis":[199],"approaches,":[200],"assign":[203],"score":[206,234,273],"piece":[209],"then":[214],"categorise":[215],"positive,":[218],"negative,":[219],"neutral.":[221],"this":[223],"normalised":[224],"score,":[226],"compare":[228],"corresponding":[232,279],"rating":[233],"investigate":[236],"potential":[238],"insights.":[240],"results":[242],"obtained":[243],"indicate":[244],"that":[245,287,291],"cannot":[248],"rely":[249],"solely":[250],"standalone":[253],"single":[254],"metric":[255],"source":[258],"truth":[260],"regarding":[261],"There":[264],"significant":[267],"difference":[268],"product.":[283],"propose":[286],"imperative":[290],"supplements":[294],"scores":[298],"strategy.":[304]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}