NSF East Asia and Pacific Summer Institute (EAPSI) for FY 2013 in Singapore

Fuhry David P, Columbus OH

Investigators

Abstract

This action funds David Fuhry of The Ohio State University to conduct a research project in the Computer and Information Science and Engineering area during the summer of 2013 at Singapore Management University's Living Analytics Research Center in Singapore. The project title is "Finding and Characterizing Communities in Online Social Networks: Utilizing Content, Links, Interactions and Affinities." The host scientist is Ee-Peng Lim. Important functions and discoveries in the social and computational sciences relate to the understanding of information networks. A fundamental task in gaining high-level knowledge from these networks is to find communities within which nodes are strongly related but between which nodes are only weakly related. In social networks these communities are found and characterized using available content, location, time and relationship information. This project addresses two sets of questions: 1) Social Media Analysis: Given large, dynamic, noisy networks, how can communities be identified and characterized, and the predictive power of discovered communities, i.e. to what extent does the behavior of a community determine or correspond with the individual behavior of its constituent users? And 2) Systems Challenges: To what extent can emerging high-performance computer architectures be utilized (e.g. using many standard processors or graphics processors in parallel within a computer, and using many networked computers in parallel) and scalable data analysis techniques (e.g. new high-performance data processing systems under active development by internet technology companies and the research community) to achieve fast, approximate results and user-driven interactive discovery on social media data? This research builds on promising initial results for fast approximate query response by transforming data according to a computational technique known as "locality-sensitive hashing," and for distinguishing community differences by a visual-analytic method of plotting communities' cumulative term (word) frequencies across local and global axes. Broader impacts of an EAPSI fellowship include providing the Fellow a first-hand research experience outside the U.S.; an introduction to the science, science policy, and scientific infrastructure of the respective location; and an orientation to the society, culture and language. These activities meet the NSF goal to educate for international collaborations early in the career of its scientists, engineers, and educators, thus ensuring a globally aware U.S. scientific workforce. Furthermore, the results - data, tools, and algorithms - are being disseminated through the publication of one or more research papers in internationally recognized social-computing research conferences, and as freely available software posted on the Fellow's web page for others to use and build on. This dissemination is consistent with the Fellow's strong track record of research paper and software publication. The Fellow's EAPSI experience will be featured in a dedicated column of The Ohio State University Department of Computer Science and Engineering department's Fall newsletter, with a circulation in the thousands of students, staff, and alumni. Outside of academia, immediately subsequent to the EAPSI fellowship the Fellow has a Fall internship at a leading U.S. social network company, Twitter, Inc. (San Francisco, CA), during which the EAPSI research results will be disseminated and to the extent possible, used to improve Twitter's capabilities.