{"id":"https://openalex.org/W4391110986","doi":"https://doi.org/10.1145/3641851","title":"Modeling a Novel Approach for Emotion Recognition Using Learning and Natural Language Processing","display_name":"Modeling a Novel Approach for Emotion Recognition Using Learning and Natural Language Processing","publication_year":2024,"publication_date":"2024-01-22","ids":{"openalex":"https://openalex.org/W4391110986","doi":"https://doi.org/10.1145/3641851"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1145/3641851","pdf_url":null,"source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":"https://doi.org/10.1145/3641851","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113101929","display_name":"Lakshmi Lalitha V.","orcid":null},"institutions":[{"id":"https://openalex.org/I179150554","display_name":"Guntur Medical College","ror":"https://ror.org/02evmt624","country_code":"IN","type":"education","lineage":["https://openalex.org/I179150554"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Lakshmi Lalitha V.","raw_affiliation_strings":["Department of Computer Science and Engineering, Guntur, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Guntur, India","institution_ids":["https://openalex.org/I179150554"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077389342","display_name":"Dinesh Kumar Anguraj","orcid":"https://orcid.org/0000-0003-2008-6828"},"institutions":[{"id":"https://openalex.org/I179150554","display_name":"Guntur Medical College","ror":"https://ror.org/02evmt624","country_code":"IN","type":"education","lineage":["https://openalex.org/I179150554"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dinesh Kumar Anguraj","raw_affiliation_strings":["Department of Computer Science and Engineering, Guntur, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Guntur, India","institution_ids":["https://openalex.org/I179150554"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":83},"biblio":{"volume":"23","issue":"3","first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9982,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9982,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.992,"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":0.9572,"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":[],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.61827075},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.5406598},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5142009},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39279667},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.37423313},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3330612},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.07878369},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1145/3641851","pdf_url":null,"source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1145/3641851","pdf_url":null,"source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"display_name":"Quality education","score":0.75,"id":"https://metadata.un.org/sdg/4"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":19,"referenced_works":["https://openalex.org/W2786205708","https://openalex.org/W2891424355","https://openalex.org/W2963324517","https://openalex.org/W2963624952","https://openalex.org/W2997775613","https://openalex.org/W3032735579","https://openalex.org/W3044680687","https://openalex.org/W3047499479","https://openalex.org/W3081599307","https://openalex.org/W3082863335","https://openalex.org/W3094312606","https://openalex.org/W3122655227","https://openalex.org/W3124604242","https://openalex.org/W3128691027","https://openalex.org/W3134181831","https://openalex.org/W3164439356","https://openalex.org/W3209629693","https://openalex.org/W4220894258","https://openalex.org/W4233571003"],"related_works":["https://openalex.org/W4391301621","https://openalex.org/W3204019825","https://openalex.org/W2931662336","https://openalex.org/W2765597752","https://openalex.org/W2748952813","https://openalex.org/W2134894512","https://openalex.org/W2085372204","https://openalex.org/W2083375246","https://openalex.org/W2077865380","https://openalex.org/W2067108088"],"abstract_inverted_index":{"Various":[0],"facts,":[1],"including":[2,279],"politics,":[3],"entertainment,":[4],"industry,":[5],"and":[6,29,53,67,102,148,195,210,223,233,241,257,283,287],"research":[7,87],"fields,":[8],"are":[9,151,229,239,285],"connected":[10],"to":[11,37,63,120,130,165],"analyzing":[12],"the":[13,49,65,72,77,96,122,126,136,149,155,169,187,191,196,213,220,226,249,253,258,268],"audience's":[14,50],"emotions.":[15,55,105,132,180],"Sentiment":[16],"Analysis":[17],"(SA)":[18],"is":[19,57,88,118,140,185,189,193,198,247,251,255,260,273],"a":[20,91,107,175],"Natural":[21],"Language":[22],"Processing":[23],"(NLP)":[24],"concept":[25],"that":[26,272],"uses":[27],"statistical":[28],"lexical":[30],"forms":[31],"as":[32,34],"well":[33],"learning":[35],"techniques":[36],"forecast":[38,131],"how":[39],"different":[40,166],"types":[41],"of":[42,59,85,178,183,205,225,245],"content":[43],"in":[44],"social":[45,80,99,137,269],"media":[46,81,100,128,138,270],"will":[47],"express":[48],"neutral,":[51],"positive,":[52],"negative":[54],"There":[56],"lack":[58],"an":[60],"adequate":[61],"tool":[62],"quantify":[64],"characteristics":[66],"independent":[68],"text":[69],"for":[70,94,114],"assessing":[71,103],"primary":[73],"audience":[74,104],"emotion":[75],"from":[76,135],"available":[78],"online":[79],"dataset.":[82],"The":[83,133,158,181,201,231,243],"focus":[84],"this":[86],"on":[89,217,236],"modeling":[90],"cutting-edge":[92],"method":[93],"decoding":[95],"connectivity":[97],"among":[98],"texts":[101],"Here,":[106],"novel":[108],"dense":[109],"layer":[110],"graph":[111],"model":[112,172,215,228],"(DLG-TF)":[113],"textual":[115,156],"feature":[116,202],"analysis":[117,203],"used":[119],"analyze":[121],"relevant":[123],"connectedness":[124],"inside":[125],"complex":[127],"environment":[129],"information":[134],"dataset":[139,271],"extracted":[141],"using":[142,212,267],"some":[143],"popular":[144],"convolution":[145],"network":[146],"models,":[147],"predictions":[150,266],"made":[152],"by":[153],"examining":[154],"properties.":[157],"experimental":[159],"results":[160],"show":[161],"that,":[162],"when":[163],"compared":[164,240],"standard":[167],"emotions,":[168],"proposed":[170],"DLG-TF":[171,211],"accurately":[173],"predicts":[174],"greater":[176],"number":[177],"possible":[179],"macro-average":[182,234,244],"baseline":[184,246],"58%,":[186],"affective":[188,250],"55%,":[190,194],"crawl":[192,254],"ultra-dense":[197,209,259],"59%,":[199],"respectively.":[200,262],"comparison":[204],"baseline,":[206],"affective,":[207],"crawl,":[208],"unsupervised":[214],"based":[216,235],"EmoTweet":[218],"gives":[219],"precision,":[221,282],"recall,":[222,281],"F1-score":[224],"anticipated":[227],"explained.":[230],"micro-":[232],"these":[237],"parameters":[238],"analyzed.":[242],"47%,":[248],"46%,":[252],"50%,":[256],"85%,":[261],"It":[263],"makes":[264],"precise":[265],"readily":[274],"available.":[275],"A":[276],"few":[277],"criteria,":[278],"accuracy,":[280],"F-measure,":[284],"assessed":[286],"contrasted":[288],"with":[289],"alternative":[290],"methods.":[291]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4391110986","counts_by_year":[],"updated_date":"2025-01-21T03:43:31.930301","created_date":"2024-01-23"}