The workshop will be compliance with the main conference - taking place virtually (a complete online event). However, the workshop dates, proceedings and publications will continue as planned.
Scope of the Workshop
This accepted workshop is to gain insights on how big data methodologies can be enhancing user understanding in the world of technology. The accepted papers will be presented in the workshop and be included in the workshop proceeding of IEEE Big Data Conference 2020.
Call for Papers
The availability of massive amounts of data has driven significant progress in the field of AI, in particular, data driven methods to understand human behavior has been an emerging topic in social science and human studies. Most internet companies need to leverage user level data from different sources to understand how users interact with their products in various scenarios and contexts. Quantitative techniques would increase generalizability of research conclusions regarding user mental models to provide frameworks for user understanding. On the other hand, large scale data can be critical to customize approaches in gaining user traction, improve user experience and monetization for different user groups. We’ve seen tremendous applications in this space, including but not limited to recommendation, marketing, online experiments, to name just a few. Fundamental understanding also requires methods such as statistical sampling, data visualization, funnel analysis, experimental design, causal inference etc.
This workshop aims to provide a platform for researchers from related fields to exchange ideas on how to use data-driven technologies for better user understanding through data analytics & modeling, experimental design and user research. The workshop will focus on both theoretical and practical challenges. Furthermore, it will place particular emphasis on algorithmic approaches in the context of learning, optimization, decision making, fairness and data privacy that raise fundamental challenges for existing techniques.
Perspective and vision papers are also welcome. 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.
The topics for the workshop including but not limited to:
- User targeting and segmentation
- Sampling methods in user research studies
- Survey methodology in user understanding
- Data utilization in Eye-tracking data
- Feedback loop to improve user experience
- Metrics and logging to describe user behaviors and experiences
- Data-driven methodology in design thinking
- Online, offline experiments and other causal inference methods
- Hierarchical modeling in user understanding
- Active learning in user success
- Fairness in user research
- Data model as framework of user mental models
- Data driven user pain points discovery and solutions
- Integrate qualitative and quantitative in user insights mining
- Data visualization in user journeys and experiences mapping
- Data integration in product development cycle
- Privacy and data protection in user research
Please submit a full-length paper (up to 10 page IEEE 2-column format) through the online submission system.
Paper Submission Page
Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to “formatting instructions” below).
8.5” x 11” (DOC, PDF)
LaTex Formatting Macros
- Oct 15, 2020: Due date for full workshop papers submission
- Nov 1, 2020: Notification of paper acceptance to authors
- Nov 15, 2020: Camera-ready of accepted papers
- Dec 10-13, 2020: Workshops
- Claire Ding, Research Scientist at Amazon
- Wutao Wei, Senior Data Scientist at Twitter
- Ying Lu, VP of Engineering, Points Technology
Program Committee Members
- Lingzhou Xue, Assistant Professor, Penn State University
- Danning Li, Assistant Professor, Jilin University
- Wenxing Ye, Sr Researcher, Google
- Wenjie Sha, Sr Software Engineer, Uber
- Danqing Xu, Manager, Statistics, AbbVie
- Owen Ho, Sr Marketing Insights Manager, Microsoft
- Alex Thayer, Head of Research, Amazon Search
- Makiko Taniguchi, Principal User Researcher, Amazon
- Qiaochu (Frank) Zhang, Research Engineer, Facebook AI
- Email: firstname.lastname@example.org