{"id":"https://openalex.org/W3088730096","doi":"https://doi.org/10.1108/ijwis-09-2019-0042","title":"Multilingual emoji prediction using BERT for sentiment analysis","display_name":"Multilingual emoji prediction using BERT for sentiment analysis","publication_year":2020,"publication_date":"2020-09-21","ids":{"openalex":"https://openalex.org/W3088730096","doi":"https://doi.org/10.1108/ijwis-09-2019-0042","mag":"3088730096"},"language":"en","primary_location":{"id":"doi:10.1108/ijwis-09-2019-0042","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijwis-09-2019-0042","pdf_url":null,"source":{"id":"https://openalex.org/S145159096","display_name":"International Journal of Web Information Systems","issn_l":"1744-0084","issn":["1744-0084","1744-0092"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Web Information Systems","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/A5004860013","display_name":"Toshiki Tomihira","orcid":null},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toshiki Tomihira","raw_affiliation_strings":["College of Knowledge and Library Sciences, University of Tsukuba, Tsukuba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Knowledge and Library Sciences, University of Tsukuba, Tsukuba, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048110544","display_name":"Atsushi Otsuka","orcid":null},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsushi Otsuka","raw_affiliation_strings":["Faculty of Library, Information and Media Science, University of Tsukuba, Tsukuba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Library, Information and Media Science, University of Tsukuba, Tsukuba, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041344867","display_name":"Akihiro Yamashita","orcid":"https://orcid.org/0000-0001-5975-9044"},"institutions":[{"id":"https://openalex.org/I4210086624","display_name":"National Institute of Technology, Tokyo College","ror":"https://ror.org/002k06d85","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210086624","https://openalex.org/I4210120810"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akihiro Yamashita","raw_affiliation_strings":["Department of Computer Science, Tokyo National College of Technology, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Tokyo National College of Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I4210086624"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110339892","display_name":"Tetsuji Satoh","orcid":null},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuji Satoh","raw_affiliation_strings":["Faculty of Library, Information and Media Studies, University of Tsukuba, Tsukuba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Library, Information and Media Studies, University of Tsukuba, Tsukuba, Japan","institution_ids":["https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.4771,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.91426764,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"16","issue":"3","first_page":"265","last_page":"280"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.992900013923645,"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/emoji","display_name":"Emoji","score":0.9673915505409241},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.8841085433959961},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8597408533096313},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7700377702713013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6668621301651001},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6387219429016113},{"id":"https://openalex.org/keywords/unicode","display_name":"Unicode","score":0.5836536884307861},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.43913891911506653},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.19535303115844727}],"concepts":[{"id":"https://openalex.org/C2779247141","wikidata":"https://www.wikidata.org/wiki/Q1049294","display_name":"Emoji","level":3,"score":0.9673915505409241},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.8841085433959961},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8597408533096313},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7700377702713013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6668621301651001},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6387219429016113},{"id":"https://openalex.org/C500551929","wikidata":"https://www.wikidata.org/wiki/Q8819","display_name":"Unicode","level":2,"score":0.5836536884307861},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.43913891911506653},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.19535303115844727},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/ijwis-09-2019-0042","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijwis-09-2019-0042","pdf_url":null,"source":{"id":"https://openalex.org/S145159096","display_name":"International Journal of Web Information Systems","issn_l":"1744-0084","issn":["1744-0084","1744-0092"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Web Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W1832693441","https://openalex.org/W2116261113","https://openalex.org/W2163605009","https://openalex.org/W2187089797","https://openalex.org/W2216973458","https://openalex.org/W2402268235","https://openalex.org/W2493916176","https://openalex.org/W2527467788","https://openalex.org/W2740582239","https://openalex.org/W2796227053","https://openalex.org/W2805755436","https://openalex.org/W2806198715","https://openalex.org/W2806221634","https://openalex.org/W2806227726","https://openalex.org/W2806771853","https://openalex.org/W2807346843","https://openalex.org/W2896457183","https://openalex.org/W2899435814","https://openalex.org/W2923978210","https://openalex.org/W2955604406","https://openalex.org/W2956147019","https://openalex.org/W2962677207","https://openalex.org/W2962947218","https://openalex.org/W2963522543","https://openalex.org/W2963712766","https://openalex.org/W2964177319","https://openalex.org/W2969845867","https://openalex.org/W3215486752"],"related_works":["https://openalex.org/W2527467788","https://openalex.org/W3005503605","https://openalex.org/W3185877708","https://openalex.org/W4210823838","https://openalex.org/W3182038225","https://openalex.org/W3080191145","https://openalex.org/W2965885965","https://openalex.org/W3041779427","https://openalex.org/W3088730096","https://openalex.org/W3160568173"],"abstract_inverted_index":{"Purpose":[0],"Recently,":[1],"Unicode":[2,126],"has":[3,17],"been":[4],"standardized":[5],"with":[6,195,207,264],"the":[7,13,88,145,153,159,204,208,225,230,235,269,273,280,283,299,318,322,332,350,363,366,373,383,387,389,398,415,420,425,432],"penetration":[8],"of":[9,15,52,63,122,139,168,188,233,244,308,365,401],"social":[10,56],"networking":[11],"services,":[12],"use":[14,419],"emojis":[16,77,154,163,169,239,245,361,430],"become":[18],"common.":[19],"Emojis,":[20],"as":[21,78,87,125,198],"they":[22,278],"are":[23,26,170,246],"also":[24,414],"known,":[25],"most":[27,351],"effective":[28,438],"in":[29,32,36,142,224,286,331,369,382],"expressing":[30],"emotions":[31,42],"sentences.":[33,44],"Sentiment":[34],"analysis":[35],"natural":[37],"language":[38],"processing":[39],"manually":[40],"labels":[41],"for":[43,179,255,427,439,452],"The":[45,61,90,117,201,258,326,345,443],"authors":[46,91,118,146,160,202,236,259,319,327,390,444],"can":[47,176,252,320,328,375],"predict":[48],"sentiment":[49,180,256],"using":[50,76,130,311,339],"emoji":[51,123,175,197,251,290,330,394,404,453],"text":[53],"posted":[54],"on":[55,98,314,392,424],"media":[57],"without":[58],"labeling":[59],"manually.":[60],"purpose":[62],"this":[64,370],"paper":[65],"is":[66,136,292,357,397,413,434,450],"to":[67,268,305,359,378,418,436],"propose":[68],"a":[69,137,148,186,199,261,306,315,337,447],"new":[70],"model":[71,206,285,422],"that":[72,162,174,196,220,238,250,277,446],"learns":[73],"from":[74,85,113,128],"sentences":[75],"labels,":[79],"collecting":[80],"English":[81],"and":[82,93,104,109,164,172,193,213,240,248,408],"Japanese":[83,407],"tweets":[84,129,141,189],"Twitter":[86,131],"corpus.":[89],"verify":[92,173,249],"compare":[94],"multiple":[95],"models":[96,210,266],"based":[97,313,423],"attention":[99],"long":[100,216],"short-term":[101,217],"memory":[102,218],"(LSTM)":[103],"convolutional":[105],"neural":[106],"networks":[107],"(CNN)":[108],"Bidirectional":[110],"Encoder":[111],"Representations":[112],"Transformers":[114],"(BERT).":[115],"Design/methodology/approach":[116],"collected":[119],"2,661":[120],"kinds":[121],"registered":[124],"characters":[127],"application":[132],"programming":[133],"interface.":[134],"It":[135],"total":[138],"6,149,410":[140],"Japanese.":[143],"First,":[144],"visualized":[147],"vector":[149,231],"space":[150,232],"produced":[151],"by":[152,155,295,335],"Word2Vec.":[156],"In":[157,297,386,410],"addition,":[158,298,411],"found":[161,237,445],"similar":[165,241],"meaning":[166,242],"words":[167,243,334],"adjacent":[171,247],"be":[177,253,302,376,437],"used":[178,254,377],"analysis.":[181,257],"Second,":[182],"it":[183,356,412],"involves":[184],"entering":[185],"line":[187],"containing":[190],"emojis,":[191],"learning":[192],"testing":[194],"label.":[200],"compared":[203,267],"BERT":[205,265,312,421],"conventional":[209,270,284],"[CNN,":[211],"FastText":[212],"Attention":[214],"bidirectional":[215,448],"(BiLSTM)]":[219],"were":[221],"high":[222],"scores":[223],"previous":[226],"study.":[227,371],"Findings":[228],"Visualized":[229],"Word2Vec,":[234],"obtained":[260],"higher":[262],"score":[263,281,300],"model.":[271],"Therefore,":[272,372],"sophisticated":[274],"experiments":[275],"demonstrate":[276],"improved":[279],"over":[282],"two":[287],"languages.":[288],"General":[289],"prediction":[291,405],"greatly":[293],"influenced":[294],"context.":[296,323],"may":[301],"lowered":[303],"due":[304],"misunderstanding":[307],"meaning.":[309],"By":[310],"bi-directional":[316],"transformer,":[317],"consider":[321],"Practical":[324],"implications":[325],"find":[329],"output":[333],"typing":[336],"word":[338],"an":[340],"input":[341],"method":[342],"editor":[343],"(IME).":[344],"current":[346],"IME":[347,380],"only":[348],"considers":[349],"latest":[352],"inputted":[353,367],"word,":[354],"although":[355,431],"possible":[358],"recommend":[360],"considering":[362],"context":[364],"sentence":[368],"research":[374],"improve":[379],"performance":[381],"future.":[384],"Originality/value":[385],"paper,":[388],"focus":[391],"multilingual":[393],"prediction.":[395,454],"This":[396],"first":[399,416],"attempt":[400,417],"comparison":[402],"at":[403],"between":[406],"English.":[409],"transformer":[426,433,449],"predicting":[428],"limited":[429],"known":[435],"various":[440],"NLP":[441],"tasks.":[442],"suitable":[451]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
