{"id":"https://openalex.org/W4412346776","doi":"https://doi.org/10.1109/kse63888.2024.11063648","title":"Detecting Emotional State of Depression in Social Media Posts Using Logistic Regression-Recursive Feature Elimination","display_name":"Detecting Emotional State of Depression in Social Media Posts Using Logistic Regression-Recursive Feature Elimination","publication_year":2024,"publication_date":"2024-11-05","ids":{"openalex":"https://openalex.org/W4412346776","doi":"https://doi.org/10.1109/kse63888.2024.11063648"},"language":"en","primary_location":{"id":"doi:10.1109/kse63888.2024.11063648","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kse63888.2024.11063648","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 16th International Conference on Knowledge and System Engineering (KSE)","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/A5100722420","display_name":"Dong Li","orcid":"https://orcid.org/0000-0002-2560-9432"},"institutions":[{"id":"https://openalex.org/I885383172","display_name":"National University of Malaysia","ror":"https://ror.org/00bw8d226","country_code":"MY","type":"education","lineage":["https://openalex.org/I885383172"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Wang Li","raw_affiliation_strings":["Universiti Kebangsaan Malaysia (UKM),Faculty of Information Science and Technology,Selangor,Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universiti Kebangsaan Malaysia (UKM),Faculty of Information Science and Technology,Selangor,Malaysia","institution_ids":["https://openalex.org/I885383172"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104679619","display_name":"Wandeep Kaur","orcid":null},"institutions":[{"id":"https://openalex.org/I885383172","display_name":"National University of Malaysia","ror":"https://ror.org/00bw8d226","country_code":"MY","type":"education","lineage":["https://openalex.org/I885383172"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Wandeep Kaur","raw_affiliation_strings":["Universiti Kebangsaan Malaysia (UKM),Faculty of Information Science and Technology,Selangor,Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universiti Kebangsaan Malaysia (UKM),Faculty of Information Science and Technology,Selangor,Malaysia","institution_ids":["https://openalex.org/I885383172"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5118955144","display_name":"Chen Wangmei","orcid":null},"institutions":[{"id":"https://openalex.org/I885383172","display_name":"National University of Malaysia","ror":"https://ror.org/00bw8d226","country_code":"MY","type":"education","lineage":["https://openalex.org/I885383172"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Chen Wangmei","raw_affiliation_strings":["Universiti Kebangsaan Malaysia (UKM),Faculty of Information Science and Technology,Selangor,Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universiti Kebangsaan Malaysia (UKM),Faculty of Information Science and Technology,Selangor,Malaysia","institution_ids":["https://openalex.org/I885383172"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.096,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.81606247,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"289","last_page":"296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.885200023651123,"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":0.885200023651123,"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":0.8601999878883362,"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/logistic-regression","display_name":"Logistic regression","score":0.819900393486023},{"id":"https://openalex.org/keywords/depression","display_name":"Depression (economics)","score":0.6038448810577393},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6018417477607727},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5614656209945679},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.4966121315956116},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.46374592185020447},{"id":"https://openalex.org/keywords/media-use","display_name":"Media use","score":0.4468308389186859},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4425358176231384},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4156065285205841},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.36415618658065796},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30359789729118347},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.17023661732673645},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.16010844707489014},{"id":"https://openalex.org/keywords/psychotherapist","display_name":"Psychotherapist","score":0.1286093294620514},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.11366388201713562}],"concepts":[{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.819900393486023},{"id":"https://openalex.org/C2776867660","wikidata":"https://www.wikidata.org/wiki/Q1814941","display_name":"Depression (economics)","level":2,"score":0.6038448810577393},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6018417477607727},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5614656209945679},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.4966121315956116},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.46374592185020447},{"id":"https://openalex.org/C3019463085","wikidata":"https://www.wikidata.org/wiki/Q1421211","display_name":"Media use","level":2,"score":0.4468308389186859},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4425358176231384},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4156065285205841},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.36415618658065796},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30359789729118347},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.17023661732673645},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.16010844707489014},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.1286093294620514},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.11366388201713562},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/kse63888.2024.11063648","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kse63888.2024.11063648","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 16th International Conference on Knowledge and System Engineering (KSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W2093051617","https://openalex.org/W2140910804","https://openalex.org/W2170505850","https://openalex.org/W2740966010","https://openalex.org/W2748108713","https://openalex.org/W2769128147","https://openalex.org/W2791577585","https://openalex.org/W2888728157","https://openalex.org/W2890929258","https://openalex.org/W2923871787","https://openalex.org/W2927148761","https://openalex.org/W2974809600","https://openalex.org/W2982086472","https://openalex.org/W3013330736","https://openalex.org/W3013908145","https://openalex.org/W3016847450","https://openalex.org/W3046477338","https://openalex.org/W3049180962","https://openalex.org/W3160692530","https://openalex.org/W3193526385","https://openalex.org/W3194388628","https://openalex.org/W3206212789","https://openalex.org/W3214457444","https://openalex.org/W3215748564","https://openalex.org/W4205705102","https://openalex.org/W4206056436","https://openalex.org/W4212968492","https://openalex.org/W4223964620","https://openalex.org/W4285304803","https://openalex.org/W4287887154","https://openalex.org/W4289259904","https://openalex.org/W4296693169","https://openalex.org/W4308085976","https://openalex.org/W4312806725","https://openalex.org/W4321611949","https://openalex.org/W4327498235","https://openalex.org/W4377200820","https://openalex.org/W6602002561","https://openalex.org/W6746503718","https://openalex.org/W6768851824","https://openalex.org/W6849184150"],"related_works":["https://openalex.org/W2129863591","https://openalex.org/W1596769710","https://openalex.org/W2923497059","https://openalex.org/W2978363435","https://openalex.org/W2086259589","https://openalex.org/W4394896199","https://openalex.org/W3217448422","https://openalex.org/W3147584709","https://openalex.org/W2351279712","https://openalex.org/W3211735916"],"abstract_inverted_index":{"With":[0],"the":[1,9,52,118,146,149,156,183,220],"rise":[2],"of":[3,12,40,55,151,203,209,222],"global":[4],"mental":[5],"health":[6],"issues":[7],"and":[8,83,105,141,155,176,193,205,215,226],"growing":[10],"use":[11],"social":[13,18,36,114,234],"media,":[14],"detecting":[15],"depression":[16,33,61,81,231],"through":[17,233],"media":[19,37,115,235],"text":[20,236],"data":[21],"has":[22],"become":[23],"increasingly":[24],"crucial.":[25],"Although":[26],"many":[27],"studies":[28,42],"have":[29],"focused":[30],"on":[31,45],"identifying":[32],"by":[34],"analyzing":[35],"texts,":[38],"most":[39],"these":[41],"mainly":[43],"focus":[44],"a":[46],"single":[47],"feature":[48,57,72,88,100,128,166,224,227],"extraction":[49,58,73,101,129,225],"technique.":[50],"However,":[51],"effective":[53,230],"combination":[54],"multiple":[56,153],"techniques":[59],"for":[60,229],"detection":[62,82,232],"remains":[63],"underexplored.":[64],"This":[65],"study":[66],"aims":[67],"to":[68,79,84,112,164],"explore":[69],"how":[70],"various":[71],"methods":[74,130],"can":[75],"be":[76],"effectively":[77],"combined":[78,107],"enhance":[80],"develop":[85],"an":[86,201,206],"optimized":[87],"selection":[89,228],"method":[90],"that":[91,171],"improves":[92],"model":[93,191],"performance":[94],"without":[95],"losing":[96],"essential":[97],"information.":[98],"Advanced":[99],"methods\u2014TFIDF,":[102],"N-gram,":[103,174],"SentiWordNet,":[104,175],"BERT\u2014were":[106],"with":[108],"machine":[109,198],"learning":[110,199],"algorithms":[111],"analyze":[113],"texts":[116],"using":[117],"eRisk":[119],"dataset.":[120],"Three":[121],"experiments":[122],"were":[123],"conductedthe":[124],"first":[125],"evaluated":[126],"individual":[127],"across":[131,195],"models":[132],"such":[133],"as":[134],"Logistic":[135,159],"Regression":[136],"(LR),":[137],"Random":[138],"Forest":[139],"(RF),":[140],"Support":[142],"Vector":[143],"Machine":[144],"(SVM);":[145],"second":[147],"assessed":[148],"effectiveness":[150],"combining":[152,172],"features;":[154],"third":[157],"applied":[158],"Regression-Recursive":[160],"Feature":[161],"Elimination":[162],"(LR-RFE)":[163],"optimize":[165],"sets.":[167],"The":[168],"results":[169],"indicated":[170],"TFIDF,":[173],"BERT":[177],"significantly":[178],"enhanced":[179,190],"performance,":[180],"particularly":[181],"in":[182],"LR":[184],"model.":[185],"Additionally,":[186],"applying":[187],"LR-RFE":[188],"further":[189],"accuracy":[192,202],"reliability":[194],"all":[196],"tested":[197],"modelsachieved":[200],"0.800":[204],"F1":[207],"score":[208],"0.7969,":[210],"which":[211],"demonstrating":[212],"improved":[213],"generalizability":[214],"robustness.":[216],"These":[217],"findings":[218],"underscore":[219],"importance":[221],"comprehensive":[223],"data.":[237]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
