[2512.09804] OnCoCo 1.0: A Public Dataset for Fine-Grained Message Classification in Online Counseling Conversations

Computer Science > Computation and Language arXiv:2512.09804 (cs) [Submitted on 10 Dec 2025 (v1), last revised 29 Mar 2026 (this version, v2)] Title:OnCoCo 1.0: A Public Dataset for Fine-Grained Message Classification in Online Counseling Conversations Authors:Jens Albrecht, Robert Lehmann, Aleksandra Poltermann, Eric Rudolph, Philipp Steigerwald, Mara Stieler View a PDF of the paper titled OnCoCo 1.0: A Public Dataset for Fine-Grained Message Classification in Online Counseling Conversations, by Jens Albrecht and 5 other authors View PDF HTML (experimental) Abstract:This paper presents OnCoCo 1.0, a new public dataset for fine-grained message classification in online counseling. It is based on a new, integrative system of categories, designed to improve the automated analysis of psychosocial online counseling conversations. Existing category systems, predominantly based on Motivational Interviewing (MI), are limited by their narrow focus and dependence on datasets derived mainly from face-to-face counseling. This limits the detailed examination of textual counseling conversations. In response, we developed a comprehensive new coding scheme that differentiates between 38 types of counselor and 28 types of client utterances, and created a labeled dataset consisting of about 2.800 messages from counseling conversations. We fine-tuned several models on our dataset to demonstrate its applicability. The data and models are publicly available to researchers and practitioners. Th...