User eXperience Perception Insights Dataset (UXPID): Synthetic User Feedback from Public Industrial Forums

Mikhail Kulyabin; Jan Joosten; Choro Ulan uulu; Nuno Miguel Martins Pacheco; Fabian Ries; Filippos Petridis; Jan Bosch; Helena Holmström Olsson

arXiv · 2509.11777

User eXperience Perception Insights Dataset (UXPID): Synthetic User Feedback from Public Industrial Forums

Mikhail Kulyabin·Jan Joosten·Choro Ulan uulu·Nuno Miguel Martins Pacheco·Fabian Ries·Filippos Petridis·Jan Bosch·Helena Holmström Olsson

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Abstract

Customer feedback in industrial forums offers rich but underexplored insights into real-world product experience. Yet systematic analysis remains challenging due to unstructured, domain-specific content and the scarcity of high-quality labeled datasets. This paper presents the User eXperience Perception Insights Dataset (UXPID), a collection of 7130 synthesized and anonymized user feedback branches extracted from a public industrial automation forum. Each JSON record contains multi-post comments enriched with metadata and annotated by a large language model (LLM) for UX insights, user expectations, severity ratings, sentiment, and topic classifications. UXPID is designed to facilitate research in user requirements, user experience (UX) analysis, and AI-driven feedback processing, particularly where privacy and licensing restrictions limit access to real-world data. It supports the training and evaluation of transformer-based models for tasks such as issue detection, sentiment analysis, and requirements extraction in technical forums, providing a valuable resource for advancing NLP methods within industrial product support and software engineering domains.

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Mikhail Kulyabin, Jan Joosten, Choro Ulan uulu, Nuno Miguel Martins Pacheco, Fabian Ries, Filippos Petridis, Jan Bosch, Helena Holmström Olsson. 2025-09-15. User eXperience Perception Insights Dataset (UXPID): Synthetic User Feedback from Public Industrial Forums. https://arxiv.org/abs/2509.11777

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