{"id":"https://openalex.org/W3023537589","doi":"https://doi.org/10.1145/3388142.3388144","title":"Sentiment and Emotion Analyses for Malaysian Mobile Digital Payment Applications","display_name":"Sentiment and Emotion Analyses for Malaysian Mobile Digital Payment Applications","publication_year":2020,"publication_date":"2020-03-09","ids":{"openalex":"https://openalex.org/W3023537589","doi":"https://doi.org/10.1145/3388142.3388144","mag":"3023537589"},"language":"en","primary_location":{"id":"doi:10.1145/3388142.3388144","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3388142.3388144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 4th International Conference on Compute and Data Analysis","raw_type":"proceedings-article"},"type":"conference-paper","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/A5041573811","display_name":"Vimala Balakrishnan","orcid":"https://orcid.org/0000-0002-6859-4488"},"institutions":[{"id":"https://openalex.org/I33849332","display_name":"University of Malaya","ror":"https://ror.org/00rzspn62","country_code":"MY","type":"education","lineage":["https://openalex.org/I33849332"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Vimala Balakrishnan","raw_affiliation_strings":["University of Malaya, Kuala Lumpur, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Malaya, Kuala Lumpur, Malaysia","institution_ids":["https://openalex.org/I33849332"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078911578","display_name":"Pravin Kumar Selvanayagam","orcid":null},"institutions":[{"id":"https://openalex.org/I33849332","display_name":"University of Malaya","ror":"https://ror.org/00rzspn62","country_code":"MY","type":"education","lineage":["https://openalex.org/I33849332"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Pravin Kumar Selvanayagam","raw_affiliation_strings":["University of Malaya, Kuala Lumpur, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Malaya, Kuala Lumpur, Malaysia","institution_ids":["https://openalex.org/I33849332"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087450075","display_name":"Lok Pik Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I33849332","display_name":"University of Malaya","ror":"https://ror.org/00rzspn62","country_code":"MY","type":"education","lineage":["https://openalex.org/I33849332"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Lok Pik Yin","raw_affiliation_strings":["University of Malaya, Kuala Lumpur, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Malaya, Kuala Lumpur, Malaysia","institution_ids":["https://openalex.org/I33849332"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I33849332"],"apc_list":null,"apc_paid":null,"fwci":0.805,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.7574652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"67","last_page":"71"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9908000230789185,"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":0.9907000064849854,"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/sentiment-analysis","display_name":"Sentiment analysis","score":0.8268349766731262},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7238719463348389},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.7211884260177612},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6931198835372925},{"id":"https://openalex.org/keywords/payment","display_name":"Payment","score":0.5803734064102173},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5623037219047546},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5307939648628235},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.5131805539131165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4803244173526764},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.4645881950855255},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4448520839214325},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34816625714302063},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.32349324226379395},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.27617132663726807},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.27581116557121277},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.12438550591468811}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.8268349766731262},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7238719463348389},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7211884260177612},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6931198835372925},{"id":"https://openalex.org/C145097563","wikidata":"https://www.wikidata.org/wiki/Q1148747","display_name":"Payment","level":2,"score":0.5803734064102173},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5623037219047546},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5307939648628235},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.5131805539131165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4803244173526764},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.4645881950855255},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4448520839214325},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34816625714302063},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32349324226379395},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.27617132663726807},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.27581116557121277},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.12438550591468811},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3388142.3388144","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3388142.3388144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 4th International Conference on Compute and Data Analysis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G8186364387","display_name":null,"funder_award_id":"FP109-2018A","funder_id":"https://openalex.org/F4320321709","funder_display_name":"Ministry of Higher Education, Malaysia"}],"funders":[{"id":"https://openalex.org/F4320321709","display_name":"Ministry of Higher Education, Malaysia","ror":"https://ror.org/05mcs2t73"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1753891864","https://openalex.org/W2069084625","https://openalex.org/W2270941958","https://openalex.org/W2277519914","https://openalex.org/W2597221078","https://openalex.org/W2603530161","https://openalex.org/W2708548069","https://openalex.org/W2730034540","https://openalex.org/W2784254609","https://openalex.org/W2861064798","https://openalex.org/W2897330266","https://openalex.org/W2995899606"],"related_works":["https://openalex.org/W2341492732","https://openalex.org/W3021501837","https://openalex.org/W4389954502","https://openalex.org/W2771255398","https://openalex.org/W2930428186","https://openalex.org/W3200027047","https://openalex.org/W4385770464","https://openalex.org/W4224262160","https://openalex.org/W3120363735","https://openalex.org/W2394323384"],"abstract_inverted_index":{"1.":[0],"Sentiment":[1],"and":[2,8,19,21,28,44,79,83,98,106,122],"emotion":[3,45,84,123],"analyses":[4,46],"provide":[5],"a":[6,49],"quick":[7],"easy":[9],"way":[10],"to":[11,26,112,133],"infer":[12],"users'":[13],"perceptions":[14],"regarding":[15],"products,":[16],"services,":[17],"topics":[18],"events,":[20],"thus":[22],"rendering":[23],"it":[24],"useful":[25],"businesses":[27],"government":[29],"bodies":[30],"for":[31,81,119,136,144],"effective":[32],"decision":[33],"making.":[34],"In":[35],"this":[36],"paper,":[37],"we":[38],"describe":[39],"the":[40,58,116,129,137,145],"outcomes":[41],"of":[42,64,74,128],"sentiment":[43,82,121],"performed":[47],"on":[48],"mobile":[50],"payment":[51],"app,":[52],"Boost,":[53],"which":[54],"is":[55],"available":[56],"in":[57],"Google":[59],"Play":[60],"Store.":[61],"A":[62,125],"total":[63],"2463":[65],"text":[66],"reviews":[67,76,130],"were":[68,77,101,131],"gathered,":[69],"however,":[70],"after":[71],"pre-processing,":[72],"1054":[73],"these":[75],"annotated":[78],"used":[80],"analyses.":[85,124],"Four":[86],"supervised":[87],"learning":[88],"algorithms,":[89],"namely,":[90],"Support":[91],"Vector":[92],"Machine,":[93],"Na\u00efve":[94],"Bayes,":[95],"Decision":[96],"Tree":[97],"Random":[99,110],"Forest":[100,111],"compared":[102],"using":[103],"Python.":[104],"Accuracy":[105],"F1":[107],"scores":[108],"indicate":[109],"have":[113],"outperformed":[114],"all":[115],"other":[117],"algorithms":[118],"both":[120],"vast":[126],"majority":[127],"found":[132],"contain":[134],"anger":[135],"negative":[138],"sentiments,":[139],"whereas":[140],"joy":[141],"was":[142],"observed":[143],"positive":[146],"reviews.":[147]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
