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The title of the keynote was: Moneyball for nanoHUB: Theory-driven and Data-driven Approaches to understand the Formation and Success of Software Development Teams For more information click here.
For more information on Syndio Social see here.
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Reference:
Xu, B., Huang, Y., & Contractor, N. (2013). Exploring Twitter networks in parallel computing environments. Presented at the XSEDE ’13: Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery, ACM Request Permissions. doi:10.1145/2484762.2484811
Abstract:
Millions of users follow each other on Twitter and form a large and complex network. The size of the network creates statistical and computational challenges on exploring and examining individual behavior on Twitter. Using a sample of 697,628 Korean Twitter users and 34 million relations, this study investigates the patterns of unfollow behavior on Twitter, i.e. people removing others from their Twitter follow lists. We use Exponential Random Graph Models (p*/ERGMs) and Statnet in R to examine the impacts of reciprocity, status, embeddedness, homophily, and informativeness on tie dissolution. We perform data processing, statistics calculation, network sampling, and Markov chain Monte Carlo (MCMC) simulation on Gordon, a unique supercomputer at the San Diego Supercomputer Center (SDSC). The process demonstrates the role of advanced computing technologies in social science studies.
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Yun Huang presented a paper “Algorithms for User Recommendation in Social Networks” in the International Network for Social Network Analysis 2013 Conference Xi’an on July 13th. This study compared four link prediction algorithms using Tencent Weibo dataset from KDD CUP 2012 (slides). The work is based on the collaboration with Chuang Zhang, Bocheng Zhu, Ming Wu, and Noshir Contractor.