WELD: The First Naturalistic Long-Period Small-Team Workplace Emotion Dataset for Ubiquitous Affective Computing

A new research dataset, WELD, has been introduced, offering the first long-period, naturalistic workplace emotion data collected from a stable small team using fully passive sensing. This dataset, comprising over 730,000 facial expression probability vectors from 49 employees of a Chinese software company over 30 months, addresses a significant gap in affective computing research by providing unique longitudinal and relational insights into workplace emotions.

This development is strategically important as it provides an unprecedented resource for understanding long-term emotional dynamics within professional settings. Such data can inform strategies for optimizing workplace well-being, team collaboration, and productivity, leveraging insights derived from advanced affective computing. It also highlights the growing capability to passively monitor and analyze human emotional states over extended periods in real-world environments.

WELD is the first dataset to combine long duration (30.1 months), naturalistic workplace context, stable small-team social structure, and fully passive sensing protocols.

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