Bulletin of the American Physical Society
APS March Meeting 2010
Volume 55, Number 2
Monday–Friday, March 15–19, 2010; Portland, Oregon
Session B13: Focus Session: Complex Networks I |
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Sponsoring Units: GSNP Chair: Alex Vespignani, Indiana University Room: B112 |
Monday, March 15, 2010 11:15AM - 11:27AM |
B13.00001: Dynamics on territorial networks: planning productive regional districts Alessandro Chessa, Marc Barthelemy, Michele Campagna, Simone Caschili, Andrea de Montis, Alessandro Vespignani We study the patterns of the communities of workers and students in the italian insular regions, by applying grouping methodologies based on the characterization of the commuter's movements as a complex weighted network. In order the get the community structure we apply an algorithm based on the maximization of the weighted modularity that allows us to detect productive, geographically located, basins at different scales and composed by towns and their territories showing a certain degree of similarity. We confront these resulting distributions of communities with relevant historical and provincial boundaries, investigate on their discrepancies and correspondences, and propose possible perspectives for local policy making and planning. The main result of this study is that the emerging community structure revealed by the network grouping algorithm matches with the actual administrative boundaries. [Preview Abstract] |
Monday, March 15, 2010 11:27AM - 11:39AM |
B13.00002: Human mobility in an emerging epidemic: a key aspect for response planning Chiara Poletto, Paolo Bajardi, Vittoria Colizza, Jose J. Ramasco, Michele Tizzoni, Alessandro Vespignani Human mobility and interactions represent key ingredients in the spreading dynamics of an infectious disease. The flows of traveling people form a network characterized by complex features, such as strong topological and traffic heterogeneities, that unfolds at different temporal and spatial scales, from short ranges to the global scale. Computational models can be developed that integrate detailed network structures based on demographic and mobility data, in order to simulate the spatial evolution of an epidemic. Focusing on the recent A(H1N1) influenza pandemic as a paradigmatic example, these approaches allow the assessment of the interplay between individual mobility and epidemic dynamics, quantifying the effects of travel restrictions in delaying the epidemic spread and the role of mobility as an additional source of information for the understanding of the early outbreak. [Preview Abstract] |
Monday, March 15, 2010 11:39AM - 11:51AM |
B13.00003: Spatial Renormalization of Human Mobility Networks Vincent J. David, Dirk Brockmann Research on human mobility networks relies on the definition of vertices (locations) and weighted links that reflect the traffic between them. Typically, the appropriate choice of spatial scale for vertices (e.g. cities, counties, regions, etc.) is arbitrary and not given by the problem at hand. It is a priori unclear how statistical and topological features depend on these choices. We investigate multi-scale human mobility networks in response to spatial renormalization, in which the spatial scale is systematically varied as vertices are locally merged to form larger meta-nodes. As a proxy for human mobility we employ the network of flux of geo-trackable items between a set of registered geographic locations (geocaches) for the US and Europe. On the finest scale these networks are sparsely connected and homogeneous, while they converge by spatial renormalization to networks with broad, invariant weight and flux distributions, potentially revealing the origin of these universal features of real human mobility networks. [Preview Abstract] |
Monday, March 15, 2010 11:51AM - 12:03PM |
B13.00004: The tomography of human mobility -- what do shortest-path trees reveal? Daniel Grady, Christian Thiemann, Dirk Brockmann Similar to illustrating the anatomy of organs using pictures of tissue slices taken at various depths, we construct shortest-path trees of different nodes to create a tomogram of large-scale mobility networks. This tomography allows us to measure global properties of the system conditioned on a reference location in the network to gain a fuller characterization of a node. Using this technqiue, we discovered a new symmetry that characterizes a large class of mobility networks. Furthermore, introducing the notion of tree similarity, we devised a new technique for clustering nodes with similar topological footprint, yielding a new, unique and efficient method for community identification in these networks and extracting their topological backbone. We applied these methods to a multi-scale human mobility network obtained from the dollar-bill-tracking site wheresgoerge.com and to the U.S. and world-wide air transportation network. [Preview Abstract] |
Monday, March 15, 2010 12:03PM - 12:15PM |
B13.00005: What scales in multiscale human mobility networks? Rafael Brune, Christian Thiemann, Dirk Brockmann Although significant research effort is currently devoted to the understanding of complex human mobility and transportation networks, their statistical features are still poorly understood. Specifically, to what extent geographical scales impose structure on these networks is largely unknown. Statistical properties of these networks have been obtained either for large scale networks or on small scale systems, indicating significant differences between the two. We will present a systematic investigation of various single scale mobility networks extracted from a comprehensive multi-scale proxy network, covering sequential length scales of a few to a few thousand kilometers. We will report that certain properties such as mobility flux distribution are universal and independent of length scale, whereas others vary systematically with scale. Furthermore we investigate the relation of a series of network characteristics as a function of scale and analyze how the different length scales interact in the embedding multiscale network. [Preview Abstract] |
Monday, March 15, 2010 12:15PM - 12:27PM |
B13.00006: Network-theoretical approach to partitioning of real power grids Ibrahim Abou Hamad, Brett Israels, Svetlana V. Poroseva, Per Arne Rikvold Modern societies depend critically on their electrical power grids. It is, therefore, essential to understand the grid's large-scale behavior in order to improve its resilience against catastrophic damage. A key factor determining the grid's large-scale behavior is its topology. In particular, an important question is whether a grid topology can be efficiently partitioned into independent communities (``islands'') of densely connected vertices (generators, substations, consumers) that are more loosely connected to other communities. Such partitioning can be utilized either to strengthen the grid by introducing new connections, or to achieve ``Intentional Intelligent Islanding'' by installing control devices in a minimal number of links in order to contain cascading failures to a limited region. Here we report on the performance of several network-partitioning algorithms, both agglomerative and spectral-based divisive, in applications to real power grids, including the high-voltage grids of Florida and Italy. [Preview Abstract] |
Monday, March 15, 2010 12:27PM - 1:03PM |
B13.00007: Complex Networks: Beyond Topology Invited Speaker: Much of the advances we witnessed in the past decade in the statistical mechanics of complex networks were inspired by maps of real networks, informing the modeling and analytical efforts. Yet, in the past few years the richness of data has improved considerably, allowing us to look deeper into the role of the nodes and links that shape the network topology and function. My goal is to move beyond the topology and review a few recent results on complex networks, from the role of distance in shaping our social networks to controllability in biological and technological networks. [Preview Abstract] |
Monday, March 15, 2010 1:03PM - 1:15PM |
B13.00008: Response of human populations to large-scale emergencies James Bagrow, Dashun Wang, Albert-L\'aszl\'o Barab\'asi Until recently, little quantitative data regarding collective human behavior during dangerous events such as bombings and riots have been available, despite its importance for emergency management, safety and urban planning. Understanding how populations react to danger is critical for prediction, detection and intervention strategies. Using a large telecommunications dataset, we study for the first time the spatiotemporal, social and demographic response properties of people during several disasters, including a bombing, a city-wide power outage, and an earthquake. Call activity rapidly increases after an event and we find that, when faced with a truly life-threatening emergency, information rapidly propagates through a population's social network. Other events, such as sports games, do not exhibit this propagation. [Preview Abstract] |
Monday, March 15, 2010 1:15PM - 1:27PM |
B13.00009: Limits of predictability in human mobility Chaoming Song, Zehui Qu, Nicholas Blumm, Albert-Laszlo Barabasi A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: to what degree is human behaviour predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual's trajectory, we find a 93\% potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, being largely independent of the distance user cover on a regular basis. We show that the origin of this deep- rooted predictability is the quantifiable regularity of human activity and discuss the potential implications of our findings. [Preview Abstract] |
Monday, March 15, 2010 1:27PM - 1:39PM |
B13.00010: Localization of social communication Dashun Wang, Chaoming Song, Albert-Laszlo Barabasi A fundamental problem in the social science and network theory is a gap between local communication and global information sharing. Due to the limited availability of empirical data, previous works on large-scale social communication mainly focused on the topological structure, lacking of knowledge on human behavior and individual activity, such as where individual lives, how far one lives from his friends, which are expected to play important roles in social communication. Here we studied the contribution of individual activity to social communication as well as the interplay between individual activity and topological structure, finding emergence of a typical communication distance between two friends, indicating a localization feature in social networks. Moreover, this localization phenomenon is associated with typological clustering, suggesting an integrating theory in understanding social behaviors. [Preview Abstract] |
Monday, March 15, 2010 1:39PM - 1:51PM |
B13.00011: Rescuing Ecosystems from Extinction Cascades Sagar Sahasrabudhe, Adilson Motter Food web perturbations stemming from climate change, overexploitation, invasive species, and natural disasters often cause an initial loss of species that results in a cascade of secondary extinctions. Using a predictive modeling framework, here we will present a systematic network-based approach to reduce the number of secondary extinctions. We will show that the extinction of one species can often be compensated by the concurrent removal of a second specific species, which is a counter-intuitive effect not previously tested in complex food webs. These compensatory perturbations frequently involve long-range interactions that are not a priori evident from local predator-prey relationships. Strikingly, in numerous cases even the early removal of a species that would eventually be extinct by the cascade is found to significantly reduce the number of cascading extinctions. Other nondestructive interventions based on partial removals and growth suppression and/or mortality increase are shown to sometimes prevent all secondary extinctions. [Preview Abstract] |
Monday, March 15, 2010 1:51PM - 2:03PM |
B13.00012: Diffusive dynamics on complex weighted networks Romualdo Pastor-Satorras, Andrea Baronchelli Diffusive processes describe a large set of phenomena occurring on natural and social systems modeled in terms of complex weighted networks. In this talk we will present a general formalism that allows to easily write down mean-field equations for any diffusive dynamics on weighted networks, and to propose the concept of an annealed weighted network, in which such equations become exact. The analysis of simple processes, such as the random walk or the Voter process, reveals a strong departure of its behavior in quenched real scale-free networks from the mean-field predictions. These observations shed light on mean-field theory on weighted networks and on its range of validity, warning about the reliability of mean-field results for more complex dynamics. [Preview Abstract] |
Monday, March 15, 2010 2:03PM - 2:15PM |
B13.00013: Opinion Formation and Consensus Engineering in Empirical Social Networks Qiming Lu, Gyorgy Korniss, Boleslaw Szymanski We study the evolution, formation, and destabilization of opinion clusters in empirical social networks. To that end, we employ the Naming Game\footnote{Baronchelli et al., J. Stat. Mech.: Theory Exp. P06014 (2006).} \footnote{Dall'Asta et al., Phys. Rev. E {\bf 74}, 036105 (2006).}, a stylized agent-based model, capturing essential features of agreement dynamics and opinion spreading in social networks. Here\footnote{Q. Lu, G. Korniss, and B.K. Szymanski, J. Econ. Interact. Coord. {\bf 4}, 221 (2009).}, we focus on on the impact that communities in the underlying social graphs can have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the late-stage behavior of the Naming Game in these networks exhibits clusters of long-living (or metastable) coexisting opinions. We then investigate various methods to destabilize coexisting metastable opinion clusters (in order to reach global consensus), such as node removal or selecting a small-number of well-positioned ``committed" agents who will stick to a preferred opinion without deviation. [Preview Abstract] |
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