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Natural language processing offers new opportunities to examine sentiment and mental health through online language in typically understudied populations.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study examined whether sentiment and cognitive features of naturalistic social media language are associated with depression diagnosis and symptom severity among midlife and older adults.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n We constructed cohorts of adults aged 50 years and older from Reddit (n=688) and Bluesky (n=210). Participants who had ever had depression and never been diagnosed were recruited via a self-report survey on Prolific that collected depression history, age of diagnosis, current symptoms, and social media handles. Public posts were preprocessed and analyzed using a validated rule-based sentiment analysis (Valence Aware Dictionary and Sentiment Reasoner). Sentiment measures were aggregated at the user level and compared by depression status within and across platforms.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n On Bluesky, users with a history of depression exhibited lower Valence Aware Dictionary and Sentiment Reasoner compound sentiment compared to users who had never been diagnosed (\u03c1=\u22120.16;\n P<\/jats:italic>\n <.001). On Reddit, current depression severity showed a small association with lower compound sentiment, and although the bootstrap CI excluded zero, the association did not remain statistically significant after correction for multiple comparisons (\n P<\/jats:italic>\n >.05). These findings indicate a platform-specific relationship between depression status and online sentiment.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Negative sentiment expressed on Bluesky was associated with depression history (ever diagnosed vs never diagnosed) among midlife and older adults. On Reddit, current depression severity showed a small association with negative sentiment that did not remain statistically significant after correction for multiple comparisons. Our findings suggest that sentiment-based language features may capture modest differences in online expression related to depression. Future work with larger samples and longitudinal symptom assessment is needed to determine whether sentiment reliably tracks with depression-related symptoms over time.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/95023","type":"journal-article","created":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T18:15:08Z","timestamp":1785435308000},"page":"e95023-e95023","source":"Crossref","is-referenced-by-count":0,"title":["Naturalistic Online Language as a Marker of Depression in Midlife and Older Adults: Computational Text Analysis of Bluesky and Reddit Posts"],"prefix":"10.2196","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8852-7602","authenticated-orcid":false,"given":"Lauren","family":"Rutter","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8159-2121","authenticated-orcid":false,"given":"Andy","family":"Edinger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7186-7344","authenticated-orcid":false,"given":"Marijn","family":"ten Thij","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8882-0243","authenticated-orcid":false,"given":"Lorenzo","family":"Lorenzo-Luaces","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2355-9881","authenticated-orcid":false,"given":"Danny","family":"Valdez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7031-9293","authenticated-orcid":false,"given":"Johan","family":"Bollen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,8,26]]},"reference":[{"issue":"1","key":"R1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-74314-3","article-title":"Depression alters the circadian pattern of online activity","volume":"10","author":"ten Thij","journal-title":"Sci Rep"},{"key":"R2","doi-asserted-by":"publisher","DOI":"10.1007\/s12144-022-04096-6","article-title":"Seeking connectedness through social media use: associations with adolescent empathic understanding and perspective-taking","volume":"42","author":"Riley","journal-title":"Curr Psychol"},{"key":"R3","doi-asserted-by":"publisher","DOI":"10.1016\/j.cobeha.2017.07.005","article-title":"Detecting depression and mental illness on social media: an integrative review","volume":"18","author":"Guntuku","journal-title":"Curr Opin Behav Sci"},{"issue":"2","key":"R4","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0272107","article-title":"Negative affect variability differs between anxiety and depression on social media","volume":"19","author":"Rutter","journal-title":"PLoS One"},{"issue":"1","key":"R5","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-28513-3","article-title":"Using language in social media posts to study the network dynamics of depression longitudinally","volume":"13","author":"Kelley","journal-title":"Nat Commun"},{"issue":"12","key":"R6","doi-asserted-by":"publisher","first-page":"1266","DOI":"10.1001\/jamapsychiatry.2019.2325","article-title":"Associations between time spent using social media and internalizing and externalizing problems among US youth","volume":"76","author":"Riehm","journal-title":"JAMA Psychiatry"},{"key":"R7","unstructured":"Share of those 65 and older who are tech users has grown in the past decade. 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