Data mining has become a critical tool for understanding human behaviors and improving user experiences in the digital age. The availability of massive amounts of user-level data from different sources has enabled technology companies to leverage quantitative techniques such as statistical sampling, data visualization, funnel analysis, user journey analysis, and experimental design to gain insights into user mental models and provide frameworks for user understanding. Large-scale data has also been crucial in customizing approaches for gaining user traction, improving user experience and monetization for different user groups. The potential applications of data mining in this space are tremendous, including recommendation, marketing, online experiments, and more.

This workshop aims to provide a platform for researchers to exchange ideas on how to use data-driven technologies for better user understanding through data analytics & modeling, experimental design, and user research. Moreover, the workshop will emphasize algorithmic approaches in the context of learning, optimization, decision making, fairness, and data privacy, which raise fundamental challenges for existing techniques. Finally, the workshop welcomes papers that describe the public release of privacy-preserving datasets that the community can use to solve fundamental technical problems of interest in user understanding.