{"id":"https://openalex.org/W4200422752","doi":"https://doi.org/10.32604/cmc.2022.022609","title":"Attention-Based Bi-LSTM Model for Arabic Depression Classification","display_name":"Attention-Based Bi-LSTM Model for Arabic Depression Classification","publication_year":2021,"publication_date":"2021-12-07","ids":{"openalex":"https://openalex.org/W4200422752","doi":"https://doi.org/10.32604/cmc.2022.022609"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2022.022609","doi":"https://doi.org/10.32604/cmc.2022.022609","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2022.022609","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2022.022609","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078056378","display_name":"Abdulqader M. Almars","orcid":"https://orcid.org/0000-0002-6822-1008","observed_orcids":["https://orcid.org/0000-0002-6822-1008","https://orcid.org/0000-0002-2292-3944"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Abdulqader M. Almars","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5078056378"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.5899,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.98199804,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"71","issue":"2","first_page":"3091","last_page":"3106"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.9961000084877014,"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":0.9961000084877014,"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":0.003800000064074993,"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":9.999999747378752e-05,"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/depression-detection","display_name":"depression detection","score":0.9879999756813049},{"id":"https://openalex.org/keywords/arabic","display_name":"Arabic language","score":0.8450000286102295},{"id":"https://openalex.org/keywords/attention-mechanism","display_name":"attention mechanism","score":0.7919999957084656},{"id":"https://openalex.org/keywords/bidirectional-lstm","display_name":"bidirectional LSTM","score":0.9810000061988831},{"id":"https://openalex.org/keywords/twitter","display_name":"Twitter","score":0.5490000247955322},{"id":"https://openalex.org/keywords/social-media-text-analysis","display_name":"social media text analysis","score":0.718999981880188},{"id":"https://openalex.org/keywords/mental-health","display_name":"mental health","score":0.6899999976158142},{"id":"https://openalex.org/keywords/text-classification","display_name":"text classification","score":0.44999998807907104}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6617597937583923},{"id":"https://openalex.org/C2780733359","wikidata":"https://www.wikidata.org/wiki/Q331769","display_name":"Mood","level":2,"score":0.6220638751983643},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5468459129333496},{"id":"https://openalex.org/C2776867660","wikidata":"https://www.wikidata.org/wiki/Q1814941","display_name":"Depression (economics)","level":2,"score":0.5423056483268738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5231243968009949},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.4993422031402588},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.4654795527458191},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4599723815917969},{"id":"https://openalex.org/C122980154","wikidata":"https://www.wikidata.org/wiki/Q205555","display_name":"Feeling","level":2,"score":0.45760297775268555},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.456976979970932},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39728879928588867},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.17964085936546326},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.1597912311553955},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.10548365116119385},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2022.022609","doi":"https://doi.org/10.32604/cmc.2022.022609","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2022.022609","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2022.022609","doi":"https://doi.org/10.32604/cmc.2022.022609","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2022.022609","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"sustainable_development_goals_aurora":[{"score":0.7799999713897705,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W30790492","https://openalex.org/W1526955519","https://openalex.org/W1537829113","https://openalex.org/W1869752048","https://openalex.org/W2004312650","https://openalex.org/W2036790583","https://openalex.org/W2064675550","https://openalex.org/W2131571251","https://openalex.org/W2131744502","https://openalex.org/W2131774270","https://openalex.org/W2133564696","https://openalex.org/W2163032431","https://openalex.org/W2172806452","https://openalex.org/W2300872908","https://openalex.org/W2470673105","https://openalex.org/W2513636044","https://openalex.org/W2517788713","https://openalex.org/W2560253731","https://openalex.org/W2562607067","https://openalex.org/W2593853439","https://openalex.org/W2740966010","https://openalex.org/W2763248665","https://openalex.org/W2767784948","https://openalex.org/W2783557991","https://openalex.org/W2800146313","https://openalex.org/W2806881496","https://openalex.org/W2809356716","https://openalex.org/W2912848870","https://openalex.org/W2914562313","https://openalex.org/W2914767245","https://openalex.org/W2915300743","https://openalex.org/W2927590866","https://openalex.org/W2947343305","https://openalex.org/W2998535576","https://openalex.org/W3000918316","https://openalex.org/W3016243233","https://openalex.org/W3017280632","https://openalex.org/W3025899167","https://openalex.org/W3043553083","https://openalex.org/W3094644839","https://openalex.org/W3097146093","https://openalex.org/W3097720646","https://openalex.org/W3131387325","https://openalex.org/W4232954355","https://openalex.org/W4252315992","https://openalex.org/W6679713772","https://openalex.org/W6686758829","https://openalex.org/W6742835619"],"related_works":["https://openalex.org/W7204237625","https://openalex.org/W4406803976","https://openalex.org/W4323894840","https://openalex.org/W4200425003","https://openalex.org/W4246885487","https://openalex.org/W4321196023","https://openalex.org/W4328010982","https://openalex.org/W4388845473","https://openalex.org/W4210455994","https://openalex.org/W4388802499"],"abstract_inverted_index":{"Depression":[0],"is":[1,141],"a":[2,9,116,162,189],"common":[3],"mental":[4],"health":[5],"issue":[6],"that":[7,55,175,213],"affects":[8],"large":[10],"percentage":[11],"of":[12,62,89,100,106,128,192],"people":[13,19,45],"all":[14],"around":[15],"the":[16,60,98,104,126,129,214,233],"world.":[17],"Usually,":[18],"who":[20],"suffer":[21],"from":[22,91],"this":[23,112],"mood":[24,33],"disorder":[25],"have":[26,75],"issues":[27],"such":[28],"as":[29,48,50,205],"low":[30],"concentration,":[31],"dementia,":[32],"swings,":[34],"and":[35,53,83,103,108,170],"even":[36],"suicide.":[37],"A":[38,131],"social":[39,63,93,121],"media":[40,64,94,122],"platform":[41],"like":[42],"Twitter":[43,190],"allows":[44],"to":[46,124,143,164,178,183],"communicate":[47],"well":[49],"share":[51],"photos":[52],"videos":[54],"reflect":[56],"their":[57],"moods.":[58],"Therefore,":[59],"analysis":[61,118],"content":[65,123],"provides":[66],"insight":[67],"into":[68],"individual":[69],"moods,":[70],"including":[71],"depression.":[72,224],"Several":[73],"studies":[74],"been":[76],"conducted":[77],"on":[78,119,167,232],"depression":[79,90,117,149,179,234],"detection":[80,88,150,235],"in":[81,85,222],"English":[82],"less":[84],"Arabic.":[86],"The":[87,152,196,225],"Arabic":[92,101,120],"lags":[95],"behind":[96],"due":[97],"complexity":[99],"language":[102],"lack":[105],"resources":[107],"techniques":[109],"available.":[110],"In":[111,181],"study,":[113],"we":[114,187],"performed":[115],"understand":[125],"feelings":[127],"users.":[130],"bidirectional":[132],"long":[133],"short-term":[134],"memory":[135],"(Bi-LSTM)":[136],"with":[137,161],"an":[138,158],"attention":[139,159],"mechanism":[140,160],"presented":[142],"learn":[144,171],"important":[145],"hidden":[146],"features":[147,169],"for":[148],"successfully.":[151],"proposed":[153,215],"deep":[154],"learning":[155,220],"model":[156,216,228],"combines":[157],"Bi-LSTM":[163,227],"simultaneously":[165],"focus":[166],"discriminative":[168],"significant":[172],"word":[173],"weights":[174],"contribute":[176],"highly":[177],"detection.":[180],"order":[182],"evaluate":[184],"our":[185],"model,":[186],"collected":[188],"dataset":[191],"approximately":[193],"6000":[194],"tweets.":[195],"data":[197],"labelling":[198],"was":[199],"done":[200],"by":[201],"manually":[202],"classifying":[203],"tweets":[204],"depressed":[206],"or":[207],"not":[208],"depressed.":[209],"Experimental":[210],"results":[211],"showed":[212],"outperformed":[217],"state-of-the-art":[218],"machine":[219],"models":[221],"detecting":[223],"attention-based":[226],"achieved":[229],"0.83%":[230],"accuracy":[231],"task.":[236]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":14}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2021-12-31T00:00:00"}