Finding local community structure in networks

Although the inference of global community structure in networks has recently become a topic of great interest in the physics community, all such algorithms require that the graph be completely known. Here, we define both a measure of local community structure and an algorithm that infers the hierarchy of communities that enclose a given vertex by exploring the graph one vertex at a time. This algorithm runs in time O(d*k^2) for general graphs when $d$ is the mean degree and k is the number of vertices to be explored. For graphs where exploring a new vertex is time-consuming, the running time is linear, O(k). We show that on computer-generated graphs this technique compares favorably to algorithms that require global knowledge. We also use this algorithm to extract meaningful local clustering information in the large recommender network of an online retailer and show the existence of mesoscopic structure.Comment: 7 pages, 6 figure

Emergence of communities and diversity in social networks

Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics.This work was supported by the National Nature Science Foundation of China under Grants 61573064, 71631002, 71401037, and 11301032; the Fundamental Research Funds for the Central Universities and Beijing Nova Programme; and the Natural Sciences and Engineering Research Council of Canada (Individual Discovery Grant). The Boston University work was supported by NSF Grants PHY-1505000, CMMI-1125290, and CHE- 1213217, and by Defense Threat Reduction Agency Grant HDTRA1-14-1-0017, and Department of Energy Contract DE-AC07-05Id14517. (61573064 - National Nature Science Foundation of China; 71631002 - National Nature Science Foundation of China; 71401037 - National Nature Science Foundation of China; 11301032 - National Nature Science Foundation of China; Fundamental Research Funds for the Central Universities and Beijing Nova Programme; Natural Sciences and Engineering Research Council of Canada (Individual Discovery Grant); PHY-1505000 - NSF; CMMI-1125290 - NSF; CHE-1213217 - NSF; HDTRA1-14-1-0017 - Defense Threat Reduction Agency; DE-AC07-05Id14517 - Department of Energy)Published versio

Report of the Global Strategy Task Force

The Global Strategy Task Force created a final report documenting its findings and recommendations. The intent of this report is to provide a framework through which the University can articulate and pursue an ambitious set of institutional goals that will increase its global connectivity and impact.To guide our work, the Task Force articulated a Global Vision for 2020:To establish Northwestern as one of the world's premier universities. To develop a culture and an infrastructure that link our intellectual communities to larger international idea and innovation networks and enable our faculty, students, and staff to lead and to learn from global advancements in research and teaching critical to human development and understanding.The Task Force identified three guiding principles for how we enact our vision.An ambitious intellectual agenda, not an economic one, must drive Northwestern's global investments. Northwestern should hire new faculty and staff, open new facilities, and initiate new dialogues and collaborations to the extent that it has a clear and compelling intellectual mission guiding each decision.Northwestern must focus on excellence to gain greater prominence in the world's leading innovation and idea networks, by identifying and investing deeply in select areas of strength and impact.Being global requires a bi-directional orientation. Northwestern must, with equal focus and vigor, expand its outward horizons while integrating global perspectives into the rich intellectual life of its US campuses and activities

Modelling fungal colonies and communities:challenges and opportunities

This contribution, based on a Special Interest Group session held during IMC9, focuses on physiological based models of filamentous fungal colony growth and interactions. Fungi are known to be an important component of ecosystems, in terms of colony dynamics and interactions within and between trophic levels. We outline some of the essential components necessary to develop a fungal ecology: a mechanistic model of fungal colony growth and interactions, where observed behaviour can be linked to underlying function; a model of how fungi can cooperate at larger scales; and novel techniques for both exploring quantitatively the scales at which fungi operate; and addressing the computational challenges arising from this highly detailed quantification. We also propose a novel application area for fungi which may provide alternate routes for supporting scientific study of colony behaviour. This synthesis offers new potential to explore fungal community dynamics and the impact on ecosystem functioning

Pioneers, subcultures and cooperatives: The grassroots augmentation of urban places

About the book: There have been numerous possible scenarios depicted on the impact of the internet on urban spaces. Considering ubiquitous/pervasive computing, mobile, wireless connectivity and the acceptance of the Internet as a non extraordinary part of our everyday lives mean that physical urban space is augmented, and digital in itself. This poses new problems as well as opportunities to those who have to deal with it. This book explores the intersection and articulation of physical and digital environments and the ways they can extend and reshape a spirit of place. It considers this from three main perspectives: the implications for the public sphere and urban public or semi-public spaces; the implications for community regeneration and empowerment; and the dilemmas and challenges which the augmentation of space implies for urbanists. Grounded with international real -life case studies, this is an up-to-date, interdisciplinary and holistic overview of the relationships between cities, communities and high technologies

Community detection in multiplex networks using locally adaptive random walks

Multiplex networks, a special type of multilayer networks, are increasingly applied in many domains ranging from social media analytics to biology. A common task in these applications concerns the detection of community structures. Many existing algorithms for community detection in multiplexes attempt to detect communities which are shared by all layers. In this article we propose a community detection algorithm, LART (Locally Adaptive Random Transitions), for the detection of communities that are shared by either some or all the layers in the multiplex. The algorithm is based on a random walk on the multiplex, and the transition probabilities defining the random walk are allowed to depend on the local topological similarity between layers at any given node so as to facilitate the exploration of communities across layers. Based on this random walk, a node dissimilarity measure is derived and nodes are clustered based on this distance in a hierarchical fashion. We present experimental results using networks simulated under various scenarios to showcase the performance of LART in comparison to related community detection algorithms

Planning and Leveraging Event Portfolios: Towards a Holistic Theory

This conceptual paper seeks to advance the discourse on the leveraging and legacies of events by examining the planning, management, and leveraging of event portfolios. This examination shifts the common focus from analyzing single events towards multiple events and purposes that can enable cross-leveraging among different events in pursuit of attainment and magnification of specific ends. The following frameworks are proposed: (1) event portfolio planning and leveraging, and (2) analyzing events networks and inter-organizational linkages. These frameworks are intended to provide, at this infancy stage of event portfolios research, a solid ground for building theory on the management of different types and scales of events within the context of a portfolio aimed to obtain, optimize and sustain tourism, as well as broader community benefits