Social Cognitive Networks Academic Research Center

The ARL Social Cognitive Network Academic Research Center (SCNARC) has been created and funded as a part of the US Army Network Science Collaborative Technology Alliance together with three other centers focusing on different kind of networks. The funding of SCNARC comes predominantly from the US Army and the Army Research Laboratory plays the key role in guiding the research directions of NS CTA. The principal member of the Center is Rensselaer Polytechnic Institute while the remaining members are CUNY, IBM TJ Watson Research Laboratory, and Northeastern University. The Center includes also collaborators from the Army Research Laboratory, Indiana University, University of Maryland, MIT, Northwestern University, University of Notre Dame and NYU. The Center will collaborate closely with other centers of the Network Science CTA.

SCNARC

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The paper on Quantifying patterns of research-interest evolution by Tao Jia, Dashun Wang, and Boleslaw K. Szymanski was publisehd in Nature Human Behavior 1(4):0078, 2017.

Mar. 22, 2017: The paper on Quantifying patterns of research-interest evolution by Tao Jia, Dashun Wang, and Boleslaw K. Szymanski was publisehd in Nature Human Behavior 1(4):0078, 2017. The authors perform a large-scale analysis of publication records, and show that changes in research interests follow a reproducible pattern characterized by an exponential distribution. They identify three fundamental features responsible for the observed exponential distribution, which arise from a subtle interplay between exploitation and exploration in research-interest evolution. They also develop a random-walk-based model that accurately reproduces the empirical observations. (more)

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The paper entitled Mobile Energy Sharing through Power Buddies, by Eyuphan Bulut, Boleslaw K. Szymanski was presented by authors at the IEEE Wireless Communications and Networking Conference (WCNC) in San Francisco, CA on March 22, 2017.

Mar. 22, 2017: The paper entitled Mobile Energy Sharing through Power Buddies, by Eyuphan Bulut, Boleslaw K. Szymanski was presented by authors at the IEEE Wireless Communications and Networking Conference (WCNC) in San Francisco, CA on March 22, 2017. Recently power sharing technologies and gadgets have emerged enabling harvesting power from other mobile devices in the user’s vicinity. The authors discuss the energy sharing in mobile social networks whose nodes are human-carried mobile devices operating on batteries. The authors propose an energy sharing model by pairing the nodes in a mobile network into power buddies. Simulation results show that a typical application scenario of (more)

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A paper on Predicting Viral News Events in Online Media by Xiaoyan Lu and Boleslaw K. Szymanski has been accepted for 2017 IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (ParSocial 2017)

Mar. 07, 2017: The information diffusion and dissemination define critical dynamics observed in large complex networks. The underlying information propagation topology, however, is often hidden or incomplete because of the lack of explicit citations of the sources. We proposed a scalable parallel algorithm to derive the node embedding to better understand the information dissemination patterns and predict emergent cascades of viral events in online media. Our algorithm infers the topic-specific output influence and the input selectivity of nodes. The parallel algorithm iteratively merges local node embedding in particular communities to obtain the global optimal results so that the processing of cascades can be significantly accelerated. (more)

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Thursday, March 9, 2017 Dr. Jonathan Z. Bakdash will present a talk at RPI on Human Machine Collarboration

Mar. 07, 2017: Dr. Jonathan Z. Bakdash is the Scientist at the Human Research and Experimentation Division of ARL at Aberdeen Proving Ground, Aberdeen, MA. Dr. Bakdash's talk on Human Machine Collaboration (also called Human Computer Collaboration and Human Agent Teaming) is a long-term R&D strategy and end-goal for the Department of Defense. In effective Human Machine Collaboration, the combination of humans + machines outperform either alone. He will focus on presenting new research ideas for Human Machine Collaboration, specifically potential applications in Causal Forecasting for event prediction (e.g., cyber attacks, social signals for emergent phenomena, tipping points in SIR models). (more)

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Prof. Boleslaw Szymanski presented an invited talk on "Algorithms for Robust Community Detection" at the University of Houston Department of Physics, March 3, 2017

Mar. 03, 2017: The talk describes two robust algorithms for community detection. The first targets communities arising in biological functions carried out by groups of interacting molecules, cells or tissues. These communities may overlap when biological components are involved in multiple functions. Moreover, they may be unstable because traditional methods are sensitive to noise and parameter settings. To address these challenges, we introduce an unorthodox clustering method called SpeakEasy, which identifies communities using top-down and bottom-up approaches simultaneously. The second algorithm is based on modularity optimization, but avoids the well-known resolution limit problem of this approach. (more)

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The Editors of the Applied Network Science journal published by Springer selected the Center's paper among four the most interesting articles published last year.

Feb. 27, 2017: The link to the announcement is http://www.springeropen.com/p/applied-network The direct link to the highlighted paper on Supporting novel biomedical research via multilayer collaboration networks by Konstantin Kuzmin, Xiaoyan Lu, Partha Sarathi Mukherjee, Juntao Zhuang, Chris Gaiteri, and Boleslaw K. Szymanski is http://appliednetsci.springeropen.com/track/pdf/10.1007/s41109-016-0015-... (more)

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Prof. Boleslaw K. Szymanski is an invited speaker at the 12th INTERNATIONAL CONFERENCE ON PARALLEL PROCESSING AND APPLIED MATHEMATICS to be held on September 10-13 in Lublin, Poland.

Feb. 27, 2017: The PPAM 2017 conference, twelfth in a series, will cover topics in parallel and distributed computing, including theory and applications, as well as applied mathematics. The focus will be on models, algorithms, and software tools which facilitate efficient and convenient utilization of modern parallel and distributed computing architectures, as well as on large-scale applications, including big data and machine learning problems. (more)

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Dr. Piotr Brodka presented a talk on “Current Challenges in the Area of Spreading Processes in Multilayer Networks”

Feb. 27, 2017: On February 23, 2017, Dr. Piotr Brodka while visiting RPI within the RENOIR project (http://renoirproject.eu/) presented a talk on “Current Challenges in the Area of Spreading Processes in Multilayer Networks”. The spreading processes in complex network and multilayer complex networks are among the fastest developing topics in modern network science. However, joining those two areas together results in the new one which is still getting its momentum. This is partially because in both areas we still have a lot to discover and understand. Thus, their merger creates uncharted space where the rules and phenomena discovered for spreading processes in simple networks very often no longer apply because of multilayer nature of networks populating this space. (more)

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A paper on Identifying Spatial Buddies to Track Lost Items by Eyuphan Bulut and Boleslaw K. Szymanski has been accepted for 2017 Workshop on SocialSens

Feb. 24, 2017: The authors study the tracking of lost objects through the collaboration among users. They analyze the visit patterns of users at the same locations and develop a metric that quantifies for each user the potential benefit of others in terms of their capability of finding that user’s lost objects. Depending on the predicted benefits, each user’s preference list of other users is formed and then utilized to identify the space buddies who can best track her lost items. The proposed system was applied to two different location based social network datasets and showed its effectiveness in different settings. (more)

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Prof. Boleslaw Szymanski presented a talk on "Social Networks and Influence through the Prism of Cognition" at the seminar at the Department of Cognitive Sciences at RPI.

Feb. 09, 2017: On February 8, 2017, Prof. Boleslaw Szymanski presented a talk on "Social Networks and Influence through the Prism of Cognition" at the research seminar of the Department of Cognitive Sciences at RPI. Prof. Szymanski discussed ties in social networks that are often represented as unweighted solid lines. Yet, human social interactions are driven by temporary events such as meeting and talking to people, exchanging information, or watching the news. Those events leave decaying-in-time traces in the human memory. The derived from such traces personal perception of the relevant events, rather than events themselves, drives human decisions and social interactions. (more)