DAPS 2016 : Data mining for the Analysis of Performance and Success

December 12, 2016

Barcelona (Spain).

Call for Papers

The First International Workshop on Data mining for the Analysis of Performance and Success (DAPS 2016) will be held in conjunction with The IEEE International Conference on Data Mining series (ICDM) on 12th Dec 2016, in Barcelona, Spain. 

The increasing availability of Big Data, able to capture diverse collective phenomena, provides an unprecedented opportunity to explore the patterns underlying success. From the strategies followed by successful sportsmen to the emergence of runaway videos on YouTube, from popularity in social media to rising starts in the scientific enterprise, from widespread technologies to groundbreaking innovations, there is wealth of data that can be explored to answer common questions: How can we measure performance? What are the common patterns of success? How did successful individuals and products get to the top? What are the principles driving the dynamics of success? These are the challenging questions at the core of the emerging Science of Success, an interdisciplinary field that is attracting scientists from different scientific backgrounds. 

The purpose of this workshop is to bring together researchers from a variety of areas, all working on the problem of analyzing and understanding the patterns of success, though from different angles. The aim is to discuss: 1) the recently developed machine learning and data mining techniques that can be leveraged to address challenges in analyzing performance and success, and 2) starting from challenges in analyzing performance and success, the practical research directions in the machine learning and data mining community.

Topics

We encourage submissions on all theoretical and practical aspects, as well as experimental studies of deployed systems. Topics of interest to the workshop include, but are not limited to, the following subject categories: 

• Science of Success
• Big Data sources for performance and success
• mathematical models of success, performance and their interplay
• ranking algorithms for performance and success
• patterns of success in the scientific enterprise
• dynamics of popularity in social media (hashtags, viral videos, etc.)
• definition and analysis of success in social networks
• measures of performance and success in sports
• data mining for sports analytics
• anomaly, doping and fraud detection in sports performance
• patterns of success in visual arts, music and writing
• adoption, diffusion and success of innovations, products and technologies
• novel approaches for detecting innovators and influencers
• performance sensing and analysis
• design of predictive models for performance and success
• opinion mining and sentiment analysis to quantify success in social media
• career success and longevity in different professions
• analysis of collective success, well-being, and development
• role of networks in success

Important Dates

Paper submission: August 01, 2016

                       

Notification of acceptance: September 13, 2016

             

Final manuscripts due: September 20, 2016

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