Emergence of scale-free leadership structure in social recommender systems

The study of the organization of social networks is important for understanding of opinion formation, rumor spreading, and the emergence of trends and fashion. This paper reports empirical analysis of networks extracted from four leading sites with social functionality (Delicious, Flickr, Twitter and YouTube) and shows that they all display a scale-free leadership structure. To reproduce this feature, we propose an adaptive network model driven by social recommending. Artificial agent-based simulations of this model highlight a "good get richer" mechanism where users with broad interests and good judgments are likely to become popular leaders for the others. Simulations also indicate that the studied social recommendation mechanism can gradually improve the user experience by adapting to tastes of its users. Finally we outline implications for real online resource-sharing systems

Link Prediction in Complex Networks: A Survey

Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent progress about link prediction algorithms, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods. We also introduce three typical applications: reconstruction of networks, evaluation of network evolving mechanism and classification of partially labelled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.Comment: 44 pages, 5 figure

Performing Under Uncertainty: Contextualized Engagement in Wildland Firefighting

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111802/1/jccm12076.pd

Cooperative Advocacy: An Approach for Integrating Diverse Perspectives in Anomaly Response

This paper contrasts cooperative work in two cases of distributed anomaly response, both from space shuttle mission control, to learn about the factors that make anomaly response robust. In one case (STS-76), flight controllers in mission control recognized an anomaly that began during the ascent phase of a space shuttle mission, analyzed the implications of the failure for mission plans, and made adjustments to plans (the flight ended safely). In this case, a Cooperative Advocacy approach facilitated a process in which diverse perspectives were orchestrated to provide broadening and cross-checks that reduced the risk of premature narrowing. In the second case (the Columbia space shuttle accident—STS-107), mission management treated a debris strike during launch as a side issue rather than a safety of flight concern and was unable to recognize the dangers of this event for the flight which ended in tragedy. In this case, broadening and cross-checks were missing due to fragmentation over the groups involved in the anomaly response process. The comparison of these cases points to critical requirements for designing collaboration over multiple groups in anomaly response situations