{"id":"https://openalex.org/W3155683087","doi":"https://doi.org/10.1109/lifetech52111.2021.9391800","title":"Efficient Creation of Japanese Tweet Emotion Dataset Using Sentence-Final Expressions","display_name":"Efficient Creation of Japanese Tweet Emotion Dataset Using Sentence-Final Expressions","publication_year":2021,"publication_date":"2021-03-09","ids":{"openalex":"https://openalex.org/W3155683087","doi":"https://doi.org/10.1109/lifetech52111.2021.9391800","mag":"3155683087"},"language":"en","primary_location":{"id":"doi:10.1109/lifetech52111.2021.9391800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lifetech52111.2021.9391800","pdf_url":null,"source":{"id":"https://openalex.org/S4306498803","display_name":"2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech)","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/A5075879599","display_name":"Tatsuki Akahori","orcid":null},"institutions":[{"id":"https://openalex.org/I5467274","display_name":"Akita Prefectural University","ror":"https://ror.org/05b1kx621","country_code":"JP","type":"education","lineage":["https://openalex.org/I5467274"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tatsuki Akahori","raw_affiliation_strings":["Akita Prefectural University, Akita, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Akita Prefectural University, Akita, Japan","institution_ids":["https://openalex.org/I5467274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032963352","display_name":"Kohji Dohsaka","orcid":null},"institutions":[{"id":"https://openalex.org/I5467274","display_name":"Akita Prefectural University","ror":"https://ror.org/05b1kx621","country_code":"JP","type":"education","lineage":["https://openalex.org/I5467274"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kohji Dohsaka","raw_affiliation_strings":["Akita Prefectural University, Akita, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Akita Prefectural University, Akita, Japan","institution_ids":["https://openalex.org/I5467274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087891899","display_name":"Masaki Ishii","orcid":"https://orcid.org/0000-0003-0687-3147"},"institutions":[{"id":"https://openalex.org/I5467274","display_name":"Akita Prefectural University","ror":"https://ror.org/05b1kx621","country_code":"JP","type":"education","lineage":["https://openalex.org/I5467274"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaki Ishii","raw_affiliation_strings":["Akita Prefectural University, Akita, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Akita Prefectural University, Akita, Japan","institution_ids":["https://openalex.org/I5467274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074846849","display_name":"Hidekatsu Ito","orcid":null},"institutions":[{"id":"https://openalex.org/I5467274","display_name":"Akita Prefectural University","ror":"https://ror.org/05b1kx621","country_code":"JP","type":"education","lineage":["https://openalex.org/I5467274"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hidekatsu Ito","raw_affiliation_strings":["Akita Prefectural University, Akita, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Akita Prefectural University, Akita, Japan","institution_ids":["https://openalex.org/I5467274"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6342,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.69685767,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"501","last_page":"505"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9988999962806702,"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":0.9947999715805054,"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/sadness","display_name":"Sadness","score":0.7783240079879761},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7453218102455139},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6986196637153625},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6674385666847229},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6482495665550232},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6222466230392456},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.5134835839271545},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.42020177841186523},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.39682507514953613},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.12574326992034912},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.10937261581420898}],"concepts":[{"id":"https://openalex.org/C2779812673","wikidata":"https://www.wikidata.org/wiki/Q169251","display_name":"Sadness","level":3,"score":0.7783240079879761},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7453218102455139},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6986196637153625},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6674385666847229},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6482495665550232},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6222466230392456},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.5134835839271545},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.42020177841186523},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.39682507514953613},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.12574326992034912},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.10937261581420898},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lifetech52111.2021.9391800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lifetech52111.2021.9391800","pdf_url":null,"source":{"id":"https://openalex.org/S4306498803","display_name":"2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W165283731","https://openalex.org/W279631868","https://openalex.org/W1518369940","https://openalex.org/W2011892903","https://openalex.org/W2109575198","https://openalex.org/W2187291759","https://openalex.org/W2761423999","https://openalex.org/W2805351602","https://openalex.org/W2805744755","https://openalex.org/W2896457183","https://openalex.org/W2963341956","https://openalex.org/W2979826702","https://openalex.org/W3098824823","https://openalex.org/W6606787761","https://openalex.org/W6610117260","https://openalex.org/W6686812563","https://openalex.org/W6755207826","https://openalex.org/W6769243733"],"related_works":["https://openalex.org/W4388134110","https://openalex.org/W2400641934","https://openalex.org/W2018346846","https://openalex.org/W2028755160","https://openalex.org/W2041541161","https://openalex.org/W3167551411","https://openalex.org/W3206592872","https://openalex.org/W2940772629","https://openalex.org/W2143086761","https://openalex.org/W2078873274"],"abstract_inverted_index":{"Emotion":[0],"recognition":[1],"in":[2,12,16,33,84],"natural":[3],"language":[4,159],"text":[5],"is":[6,182],"one":[7],"of":[8,20,72,105,113,131,137,168],"the":[9,13,49,65,70,88,123,128,135,144,173,185],"critical":[10],"technologies":[11],"human-computer":[14],"interface":[15],"a":[17,30,40,96,153,156,166],"wide":[18],"range":[19],"fields,":[21],"including":[22],"health":[23],"and":[24,26,55,77,108,116,134,171],"well-being,":[25],"labeled":[27],"data":[28,138],"plays":[29],"significant":[31],"role":[32],"developing":[34],"such":[35],"technology.":[36],"This":[37],"paper":[38],"presents":[39],"method":[41,89,125,181],"for":[42,110,184],"efficiently":[43],"collecting":[44],"Japanese":[45,91,97,174],"emotion":[46,51,106,148,176,186],"tweets":[47,67,102,133],"carrying":[48],"first-person's":[50],"using":[52,155,165],"emotional":[53],"expressions":[54],"sentence-final":[56,60],"expressions.":[57],"By":[58,86],"exploiting":[59],"expressions,":[61],"we":[62,94],"can":[63,126],"identify":[64],"targeted":[66,132],"even":[68],"though":[69],"subjects":[71],"sentences":[73],"are":[74,80],"often":[75,81],"omitted,":[76],"first-person":[78],"pronouns":[79],"not":[82],"explicitly":[83],"Japanese.":[85],"applying":[87],"to":[90],"tweet":[92,98,175],"data,":[93],"constructed":[95,178],"dataset":[99,145,177],"comprising":[100],"2,234":[101],"with":[103],"labels":[104],"types":[107,112],"intensities":[109],"two":[111],"emotions:":[114],"joy":[115],"sadness.":[117],"The":[118],"evaluation":[119],"results":[120],"show":[121,151],"that":[122,146,152,172],"proposed":[124],"improve":[127],"collection":[129],"efficiency":[130],"reliability":[136],"labels.":[139],"We":[140,150],"developed":[141],"classifiers":[142],"from":[143],"recognize":[147],"intensities.":[149],"classifier":[154],"deep":[157],"learning-based":[158],"model":[160,170],"outperforms":[161],"conventional":[162],"baseline":[163],"methods":[164],"Bag":[167],"Words":[169],"by":[179],"our":[180],"useful":[183],"intensity":[187],"recognition.":[188]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
