The 3rd Annual Workshop on Big Data Technology and Ethics Considerations in Customer Behavior and Customer Feedback Mining 
(BEBF 2018) 
In conjunction with 2018 IEEE International Conference on Big Data (IEEE BigData 2018)

Introduction to Workshop

Customer Behavior and Customer Feedback Mining is Norm of Business

For any business and organization, studying customer activity and behavior has becoming more and more essential and impactful. Businesses want to learn how its users respond to or use their products, in order to provide actionable insights for key business decision: testing new products or features, refining existing versions or initiating new marketing campaigns. Collecting and studying user behavior data helps companies/organizations better target their efforts. Furthermore, customer feedback, as the most direct representative of user experience, is essential for improving the quality of its products or services. Breakthroughs and advancements in communication technology and social media has been playing a profound role in enhancing the capabilities of companies and organizations to understand their customers. The history sees the advancements from speech to ancient cave paintings to all sorts of social media such as Skype, WhatsApp, Facebook, Twitter, etc.; from speech interviews to paper surveys to call center services to online reviews or chats to feedback systems to social media discussion platforms. Customer behavior and feedback mining through a variety of data sources including both structural and unstructured data is crucial to the emerging tasks for businesses, e.g. department stores and commercial companies in understanding and optimizing user engagement and user’s attitudes towards their products and services.

As increasingly high volumes of customer activity and customer feedback data become available to companies daily in different forms, more intelligent and automated big data analytic mechanisms become critically in need to mine both user activity patterns and feedback. For instance, sequential time-series customer activities and user network data is extremely large, giving rise to large memory consumption and computing time in the analytic system. In addition, textual customer feedback data is extremely noisy with lots of slang, dirty words, misspellings, and incorrectly translated texts, etc. because users all over the world can provide feedback. Big Data analytic technology in customer behavior and feedback mining has been a powerful weapon to solve these problems.

Ethics Considerations in Customer Behavior and Customer Feedback Mining

Ethics and privacy have been a long time concerns in human computer interaction – from AI research to data mining practice, the fear of technology getting out of control has been a worry for a long time. With the improved capability and availability of big data collection, storage, access and sharing, and big data analytics and deep learning fever, in particular NLP enabled unstructured text understanding, ethics consideration in the entire process of customer behavior and customer feedback mining become more urgent and prominent. We would like to attract research and exploration of ethics considerations in the process of data collection, fusion and enrichment, analytics and deep learning process, and in the applications of findings from such activities to business activities.

Workshop Motivation

This workshop is a continuation and expansion of our workshop from IEEE BigData 2016: Customer Feedback Mining and Transfer Learning. We expand the workshop to include both Customer Behavior mining and Customer Feedback mining, in particular we include ethics considerations in the mining process, and in application findings from mining to business decisions.

The rapidly increasing attention to customer behavior and satisfaction by department stores and commercial companies and development in social media as well as online systems has promoted production and research in user engagement pattern recognition, user network analysis, topic detection from customer feedback, text-based sentiment analysis, etc. With the development of Internet of Things and social media network, ethics considerations has also playing an important role in application of big data, especially customer behavior and feedback mining. It is meaningful to hold this workshop to provide a platform for professionals, researchers, engineers, and data scientists to share opinions and exchange ideas, so as to enhance the research and production in both techniques and practical ethics considerations in customer behavior and feedback mining, the advancement in the communication between customers and companies, and the improvement of the quality of the world-wide products and service.

Workshop Organizers

General Chairs

·       Xin Deng, Data Scientist, Microsoft | Skype, Redmond, WA

·       Ross Smith, Principal Director of Engineering, Microsoft | Skype, Redmond, WA

·       Yan Guo, Principal Data Insights & Intelligence Manager, Microsoft | Skype, Redmond, WA


Program Chairs

·       Xin Deng, Data Scientist, Microsoft | Skype, Redmond, WA

·       Yan Guo, Principal Data Insights & Intelligence Manager, Microsoft | Skype, Redmond, WA


Primary Contact:

·       Xin Deng, xinde@microsoft.com


Alternate Contact:

·       Ross Smith, rosss@microsoft.com

·       Yan Guo, yagu@microsoft.com

Program Committee Members

·     Robert Musson, Principal Data Scientist, Microsoft, WA, Robert.Musson@microsoft.com

·       Xin Deng, Data Scientist, Microsoft | Skype, Redmond, WA, xinde@microsoft.com

·       Donghui Wu, Vice president of Technology, PCCI, Dallas, TX, donghuiwu@hotmail.com 

      ·     Stephen Sherman, Data Scientist, Microsoft, WA, Stephen.Sherman@microsoft.com

       ·       Wutao Wei, Data Scientist, Microsoft, Redmond, WA, wutwei@microsoft.com

·       Ben Olsen, Director of Analytics and Data Visualization, Matisia Consultants, WA, ben@analyticsguild.com

·     Jingfen Zhang, Research Scientist, Amazon, WA, zhangjingf@gmail.com

·     Wei Lu, Applied Scientist, Amazon, WA, luwei.blues@gmail.com

Important Dates

Oct.10, 2018: Due date for full workshop papers submission

Nov.1, 2018: Notification of paper acceptance to authors

Nov.15, 2018: Camera-ready of accepted papers

Dec.10-13, 2018: Workshop