@inproceedings{tabusca-etal-2026-visibility,
    title = "The Visibility of Depression in Social Media: Mapping Symptoms to Linguistic Features",
    author = "T{\u{a}}bușc{\u{a}}, Ștefana-Arina  and
      Uban, Ana Sabina  and
      Dinu, Liviu",
    editor = "Zirikly, Aya  and
      Bar, Kfir  and
      MacAvaney, Sean  and
      Ireland, Molly  and
      Ophir, Yaakov  and
      Atzil-Slonim, Dana  and
      Varadarajan, Vasudha  and
      Bedrick, Steven  and
      Desmet, Bart",
    booktitle = "Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology ({CLP}sych 2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.clpsych-1.28/",
    pages = "355--361",
    ISBN = "979-8-89176-421-7",
    abstract = "Digital phenotyping research assumes that depression symptoms are detectable in people{'}s written discourse, yet there is room to explore which specific symptoms leave linguistic traces and which remain invisible. In this paper, using matched clinical and social media data from 169 Reddit users (eRisk 2021), we construct a clinical symptom network from BDI-II responses and a symptom-language bridge matrix mapping each of the 21 BDI-II symptoms to 15 curated LIWC-22 linguistic features. After FDR correction, 37 significant associations emerge, revealing a divide between cognitive-affective symptoms (sadness, worthlessness, suicidality) that leave clear linguistic traces through mental health vocabulary, anxiety words, and first-person pronouns, while others, like vegetative symptoms (sleep, appetite, irritability, libido) appear less visible. These findings suggest that there might be dimensions of depression that are missed by text-based depression monitoring."
}