{"id":"https://openalex.org/W7124177977","doi":"https://doi.org/10.1145/3777577.3777579","title":"MLEF: Multi-Level Emotion Feature Representation for Depression Detection Leveraging Fine-Grained Emotion Lexicon","display_name":"MLEF: Multi-Level Emotion Feature Representation for Depression Detection Leveraging Fine-Grained Emotion Lexicon","publication_year":2025,"publication_date":"2025-10-24","ids":{"openalex":"https://openalex.org/W7124177977","doi":"https://doi.org/10.1145/3777577.3777579"},"language":null,"primary_location":{"id":"doi:10.1145/3777577.3777579","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3777577.3777579","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 6th International Symposium on Artificial Intelligence for Medical Sciences","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3777577.3777579","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123017383","display_name":"Shuangwei Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuangwei Tang","raw_affiliation_strings":["Anhui University, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"Anhui University, Hefei, Anhui, China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5123017383"],"corresponding_institution_ids":["https://openalex.org/I143868143"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78082156,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.8744999766349792,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social 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/T12488","display_name":"Mental Health via Writing","score":0.8744999766349792,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social 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":0.0868000015616417,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.012799999676644802,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7735999822616577},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.7422999739646912},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.6152999997138977},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5873000025749207},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5679000020027161},{"id":"https://openalex.org/keywords/emotion-detection","display_name":"Emotion detection","score":0.49570000171661377},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.48399999737739563},{"id":"https://openalex.org/keywords/mainstream","display_name":"Mainstream","score":0.45669999718666077},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4066999852657318}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7735999822616577},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.7422999739646912},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.6152999997138977},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5873000025749207},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5770999789237976},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5679000020027161},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.5187000036239624},{"id":"https://openalex.org/C2988148770","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion detection","level":3,"score":0.49570000171661377},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.48399999737739563},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.48260000348091125},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.48179998993873596},{"id":"https://openalex.org/C2777617010","wikidata":"https://www.wikidata.org/wiki/Q18957","display_name":"Mainstream","level":2,"score":0.45669999718666077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43810001015663147},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4066999852657318},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.40059998631477356},{"id":"https://openalex.org/C6438553","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Affective computing","level":2,"score":0.37689998745918274},{"id":"https://openalex.org/C2776671715","wikidata":"https://www.wikidata.org/wiki/Q655170","display_name":"Mental lexicon","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C143110190","wikidata":"https://www.wikidata.org/wiki/Q5373787","display_name":"Emotional expression","level":2,"score":0.33739998936653137},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C558461103","wikidata":"https://www.wikidata.org/wiki/Q154430","display_name":"Anxiety","level":2,"score":0.326200008392334},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C96199812","wikidata":"https://www.wikidata.org/wiki/Q2145290","display_name":"Mental representation","level":3,"score":0.3018999993801117},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C2776867660","wikidata":"https://www.wikidata.org/wiki/Q1814941","display_name":"Depression (economics)","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2581999897956848},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3777577.3777579","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3777577.3777579","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 6th International Symposium on Artificial Intelligence for Medical Sciences","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3777577.3777579","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3777577.3777579","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 6th International Symposium on Artificial Intelligence for Medical Sciences","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6619839668273926,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2040467972","https://openalex.org/W2748108713","https://openalex.org/W2798684758","https://openalex.org/W3157024423","https://openalex.org/W3190686212","https://openalex.org/W3206212789","https://openalex.org/W4280563542","https://openalex.org/W4283164527","https://openalex.org/W4285211483","https://openalex.org/W4290098820","https://openalex.org/W4311908682","https://openalex.org/W4321854778","https://openalex.org/W4367146937","https://openalex.org/W4393152832","https://openalex.org/W4404782045"],"related_works":[],"abstract_inverted_index":{"Depression":[0],"is":[1],"a":[2,17,110,135,146],"prevalent":[3],"mental":[4],"health":[5],"condition,":[6],"and":[7,42,52,71,98,158,167,183,205,217,224],"by":[8,61,128,179],"analyzing":[9,30,180],"social":[10],"posts":[11],"to":[12,20,77,83,94,100,138,160],"detect":[13],"depression":[14,191],"can":[15],"be":[16],"promising":[18],"approach":[19],"address":[21,104],"this":[22,105,107],"issue.":[23],"Currently,":[24],"mainstream":[25,201],"detection":[26],"methods":[27,57],"focus":[28],"on":[29,193,198],"how":[31],"people":[32],"express":[33],"themselves":[34],"in":[35,88],"posts,":[36,55],"including":[37],"the":[38,43,50,84,130,173,176,199],"content":[39],"they":[40,45],"write":[41],"emotions":[44],"convey.":[46],"However,":[47],"when":[48],"modeling":[49],"language":[51,164,182],"emotion":[53,101,112,118,126,184],"of":[54,132,175],"these":[56],"are":[58],"often":[59],"limited":[60],"coarse":[62],"emotional":[63,85,91,141,168,194],"granularity,":[64],"such":[65],"as":[66],"only":[67],"distinguishing":[68],"between":[69],"positive":[70],"negative":[72],"emotions,":[73,219],"making":[74],"it":[75],"difficult":[76],"capture":[78,139],"subtle":[79,140],"depressive":[80],"emotions.":[81],"According":[82],"granularity":[86,92,195],"theory":[87],"psychology,":[89],"finer":[90],"contributes":[93],"more":[95],"accurate":[96],"identification":[97],"response":[99],"issues.":[102],"To":[103],"issue,":[106],"paper":[108],"proposes":[109],"multi-level":[111,177],"feature":[113,147],"representation":[114],"method":[115],"leveraging":[116],"fine-grained":[117,136,218],"lexicon":[119,137],"called":[120],"MLEF.":[121],"First,":[122],"we":[123,144,171],"leveraged":[124],"existing":[125],"lexicons":[127],"increasing":[129],"number":[131],"categories,":[133],"constructing":[134],"differences.":[142],"Then,":[143],"designed":[145],"extraction":[148],"framework":[149],"that":[150,208],"integrates":[151],"features":[152,178],"at":[153],"three":[154],"levels:":[155],"word,":[156],"topic,":[157],"user,":[159],"comprehensively":[161],"characterize":[162],"users'":[163],"expression":[165,215],"habits":[166,216],"tendencies.":[169],"Additionally,":[170],"explored":[172],"interpretability":[174],"underlying":[181],"patterns,":[185],"providing":[186],"new":[187],"insights":[188],"into":[189],"understanding":[190],"based":[192],"theory.":[196],"Experiments":[197],"two":[200],"public":[202],"datasets,":[203],"eRisk2017":[204],"eRisk2018,":[206],"demonstrate":[207],"MLEF":[209],"successfully":[210],"captures":[211],"depressed":[212],"individuals'":[213],"linguistic":[214],"significantly":[220],"improving":[221],"classification":[222],"performance":[223],"surpassing":[225],"previous":[226],"best-reported":[227],"results.":[228]},"counts_by_year":[],"updated_date":"2026-01-15T23:21:31.212559","created_date":"2026-01-15T00:00:00"}
