[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83985-en":3,"doc-seo-83985-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},83985,7971461740886,"Theodore","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","Population-Level Profiling of DSM-5 Depressive Symptoms Among Self-Reported ADHD and ASD Users on Twitter","The study investigates how social media users who self-report ADHD and ASD express DSM-5 depressive symptoms in their tweets, and whether detected differences hold under multiple levels of depressive-content filtering. Using 1,282,437 tweets from 792 diagnosis-disclosure users, tweets are filtered via zero-shot NLI and classified into nine DSM-5 symptom categories with MentalRoBERTa fine-tuned on ReDSM5. L1-penalised logistic regression and symptom co-occurrence correlations quantify group-level patterns and robustness.","arXiv :2607 .05626v 1 [ cs .CL] 6 Jul 2026  \nPopulation-Level Profiling of DSM-5 Depressive Symptoms Among Self-Reported ADHD and ASD Users on Twitter: An Exploratory Study Using Advanced NLP and Statistical  \nAnalysis  \nMuhammad Rizwan, PhD 1 , David Nabergoj, MSc 1 , and Jure Demšar, PhD 1  \n1Faculty of Computer and Information Science, University of Ljubljana, Slovenia  \nCorresponding author:  \nMuhammad Rizwan  \nFaculty of Computer and Information Science  \nUniversity of Ljubljana  \nVena pot 113, Ljubljana 1000, Slovenia  \n[Email: muhammad.rizwan@fri.uni-lj.si](Email: muhammad.rizwan@fri.uni-lj.si)  \nAbstract  \nBackground: Depression frequently co-occurs with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) . However, population-level differences in how depressive symptoms are expressed between these groups remains underexplored.  \nObjective: This study examined whether social media users with ADHD and ASD differ in how they express Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) depressive symptoms in their tweets, focusing on the relative prominence of the nine symptoms at population level and testing whether observed differences persist across varying levels of depressive-content filtering.  \nMethods: We analysed 1,282,437 tweets from 792 users (622 ADHD; 170 ASD) from a diagnosisdisclosure Twitter dataset. Tweets were pre-filtered for depressive relevance using zero-shot NLI, then classified into nine DSM-5 depressive symptoms using MentalRoBERTa fine-tuned on ReDSM5 (an expert annotated dataset) . Nine-symptom profiles were created and mean-centered per user. We applied L1-penalised logistic regression with 5-fold cross-validation to distinguish between ADHD and ASD users, complemented by Pearson correlations to assess symptom co-occurrence. We tested the robustness of our approach across five filtering thresholds (0.45–0.65) using 1,000-resample bootstrapping and cross-threshold sign consistency.  \nResults: For multi-label depression symptom classification, MentalRoBERTa achieved macro-F1 of 0.901 on a held-out set (≥ 0.85 F1 on 8/9 symptoms), substantially outperforming the original ReDSM5 benchmark. ADHD vs ASD classification using fitted logistic regression yielded stable but modest performance (cross-validated ROC-AUC 0.645–0.653 across thresholds) . Coefficient analysis revealed that cognitive issues, sleep issues, appetite change, and fatigue consistently leaned toward ADHD, while suicidal ideation and anhedonia consistently leaned toward ASD (bootstrap selection ≥ 0.90 across all thresholds) . Psychomotor disturbance showed the same ASD-leaning directional effect with slightly lower stability. Correlation analysis revealed a largely shared symptom co-occurrence structure between groups (17 of 36 pairs individually bootstrap-robust in both groups and in the same direction); no pair met our pre-specified criterion for a robust disorder-specific difference.  \nConclusions: Population-level differences in depression-related language between self-reporting social media users with ADHD and ASD were consistently observed across multiple analytic thresholds, indicating distinct patterns of depressive symptom expression. These differences reflect population-level reproducibility rather than clinical validity and should be interpreted as exploratory rather than as evidence of differing depressive phenomenology at the individual level.  \nKeywords: depression; DSM-5; ADHD; autism spectrum disorder; digital phenotyping; MentalRoBERTa;  \nsocial media; natural language processing; Twitter.  \n1 Introduction  \nMajor depressive disorder is one of the most common psychiatric comorbidities in both attention-deficit/hyperactivity  \ndisorder (ADHD) [1, 22] and autism spectrum disorder (ASD) [2, 25], two highly prevalent and frequently co-occurring neurodevelopmental conditions [23, 24] . Epidemiological work has consistently reported elevated rates of depressive symptoms ","cbCaiabDXtWyOiS9","https://ap.wps.com/l/cbCaiabDXtWyOiS9","pdf",870636,1,23,"English","en",105,"# Abstract\n# Introduction\n## Comorbidity and symptom phenomenology\n## Motivation and prior work\n## Study approach (NLP and statistical analysis)","[{\"question\":\"What is the main objective of the study?\",\"answer\":\"To determine whether self-reported ADHD and ASD social media users differ in how they express the nine DSM-5 depressive symptoms in tweets, and whether those differences remain consistent across filtering thresholds.\"},{\"question\":\"How were tweets processed and mapped to DSM-5 depressive symptoms?\",\"answer\":\"Tweets were pre-filtered for depressive relevance using zero-shot NLI, then classified into nine DSM-5 depressive symptoms using MentalRoBERTa fine-tuned on ReDSM5.\"},{\"question\":\"Which depressive symptoms showed stable directional differences between ADHD and ASD groups?\",\"answer\":\"Cognitive issues, sleep issues, appetite change, and fatigue leaned toward ADHD, while suicidal ideation and anhedonia leaned toward ASD across all thresholds; psychomotor disturbance showed a similar ASD-leaning effect with slightly lower stability.\"}]",1784191852,58,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":27},"population-level-profiling-of-dsm-5-depressive-symptoms-among-self-reported-adhd-and-asd-users-on-twitter","",{"@graph":35,"@context":85},[36,53,68],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/population-level-profiling-of-dsm-5-depressive-symptoms-among-self-reported-adhd-and-asd-users-on-twitter/83985/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-17","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main objective of the study?","Question",{"text":75,"@type":76},"To determine whether self-reported ADHD and ASD social media users differ in how they express the nine DSM-5 depressive symptoms in tweets, and whether those differences remain consistent across filtering thresholds.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How were tweets processed and mapped to DSM-5 depressive symptoms?",{"text":80,"@type":76},"Tweets were pre-filtered for depressive relevance using zero-shot NLI, then classified into nine DSM-5 depressive symptoms using MentalRoBERTa fine-tuned on ReDSM5.",{"name":82,"@type":73,"acceptedAnswer":83},"Which depressive symptoms showed stable directional differences between ADHD and ASD groups?",{"text":84,"@type":76},"Cognitive issues, sleep issues, appetite change, and fatigue leaned toward ADHD, while suicidal ideation and anhedonia leaned toward ASD across all thresholds; 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