What Life Events are Disclosed on Social Media, How, When, and By Whom?
Koustuv Saha, Jordyn Seybolt, Stephen M. Mattingly, Talayeh Aledavood, Chaitanya Konjeti, Gonzalo J. Martínez, Ted Grover, Gloria Mark, Munmun De Choudhury
Abstract
Social media platforms continue to evolve as archival platforms, where important milestones in an individual’s life are socially disclosed for support, solidarity, maintaining and gaining social capital, or to meet therapeutic needs. However, a limited understanding of how and what life events are disclosed (or not) prevents designing platforms to be sensitive to life events. We ask what life events individuals disclose on a 256 participants’ year-long Facebook dataset of 14K posts against their self-reported life events. We contribute a codebook to identify life event disclosures and build regression models on factors explaining life events’ disclosures. Positive and anticipated events are more likely, whereas significant, recent, and intimate events are less likely to be disclosed on social media. While all life events may not be disclosed, online disclosures can reflect complementary information to self-reports. Our work bears practical and platform design implications in providing support and sensitivity to life events.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 43541fb0-f669-4249-96c4-9096adc97768Cited by top-tier papers12
- Charting the Sociotechnical Gap in Explainable AI: A Framework to Address the Gap in XAIUpol Ehsan, Koustuv Saha, Munmun De Choudhury, Mark O. RiedlCSCW 2023 · 84 citations
- Metamorpheus: Interactive, Affective, and Creative Dream Narration Through Metaphorical Visual StorytellingQian Wan, Xin Feng, Yining Bei, Zhiqi Gao et al.CHI 2024 · 34 citations
- What is Sensitive About (Sensitive) Data? Characterizing Sensitivity and Intimacy with Google Assistant UsersAlejandra Gómez Ortega, Jacky Bourgeois, Gerd KortuemCHI 2023 · 33 citations
- Mental Health Coping Stories on Social Media: A Causal-Inference Study of Papageno EffectYunhao Yuan, Koustuv Saha, Barbara Keller, Erkki Tapio Isometsä et al.WWW 2023 · 29 citations
- Veteran Critical Theory as a Lens to Understand Veterans' Needs and Support on Social MediaJiawei Zhou, Koustuv Saha, Irene Michelle Lopez Carron, Dong Whi Yoo et al.CSCW 2022 · 27 citations
Builds on1
Related papers
- Tracking Life's Ups and Downs: Mining Life Events from Social Media Posts for Mental Health AnalysisMinghao Lv, Siyuan Chen, Haoan Jin, Minghao Yuan et al.ACL 2025 · 4 citations
- Distress Disclosure across Social Media Platforms during the COVID-19 Pandemic: Untangling the Effects of Platforms, Affordances, and AudiencesRenwen Zhang, Natalya N. Bazarova, Madhu C. ReddyCHI 2021 · 50 citations
- Contextual Gaps in Machine Learning for Mental Illness Prediction: The Case of Diagnostic DisclosuresStevie Chancellor, Jessica L. Feuston, Jayhyun ChangCSCW 2023 · 6 citations
- Understanding User Experience of Support-Seeking on Reddit During Stressful TimesJiayu Yuki Yin, Novia Wong, Madhu C. ReddyCSCW 2025 · 2 citations
- Chirp: The Impact of Private Online Self-Disclosure on Perceived Social SupportTalie Massachi, John Roy, Lauren Choi, Gabriela Hoefer et al.CSCW 2024 · 4 citations
