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154
Relating network topology to the robustness of centrality measures
, 2005
"... This paper reports on a simulation study of social networks that investigated how network topology relates to the robustness of measures of system-level node centrality. This association is important to understand as data collected for social network analysis is often somewhat erroneous and may—to a ..."
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Cited by 9 (4 self)
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This paper reports on a simulation study of social networks that investigated how network topology relates to the robustness of measures of system-level node centrality. This association is important to understand as data collected for social network analysis is often somewhat erroneous and may—to an unknown degree—misrepresent the actual true network. Consequently the values for measures of centrality calculated from the collected network data may also vary somewhat from those of the true network, possibly leading to incorrect suppositions. To explore the robustness, i.e., sensitivity, of network centrality measures in this circumstance, we conduct Monte Carlo experiments whereby we generate an initial network, perturb its copy with a specific type of error, then compare the centrality measures from two instances. We consider the initial network to represent a true network, while the perturbed represents the observed network. We apply a six-factor full-factorial block design for the overall methodology. We vary several control variables (network topology, size and density, as well as error type, form and level) to generate 10,000 samples each from both the set of all possible networks and possible errors within the parameter space. Results show that the topology of the
Animating the Development of Social Networks over Time using a Dynamic Extension of Multidimensional Scaling. El Profesional de la Información
, 2008
"... The animation of network visualizations poses technical and theoretical challenges. Rather stable patterns are required before the mental map enables a user to make inferences over time. In order to enhance stability, we developed an extension of stressminimization with developments over time. This ..."
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Cited by 9 (6 self)
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The animation of network visualizations poses technical and theoretical challenges. Rather stable patterns are required before the mental map enables a user to make inferences over time. In order to enhance stability, we developed an extension of stressminimization with developments over time. This dynamic layouter is no longer based on linear interpolation between independent static visualizations, but change over time is used as a parameter in the optimization. Because of our focus on structural change versus stability the attention is shifted from the relational graph to the latent eigenvectors of matrices. The approach is illustrated with animations for the journal citation environments of Social Networks, the (co-)author networks in the carrying community of this journal, and the topical development using relations among its title words. Our results are also compared with animations based on PajekToSVGAnim and SoNIA.
Systemic Risk from Global Financial Derivatives: A Network Analysis of Contagion and Its Mitigation with Super-Spreader Tax
"... This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to eli ..."
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Cited by 8 (3 self)
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This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate. Financial network analysis is used to provide firm level bottom-up holistic visualizations of interconnections of financial obligations in global OTC derivatives markets. This helps to identify Systemically Important Financial Intermediaries (SIFIs), analyse the nature of contagion propagation, and also monitor and design ways of increasing robustness in the network. Based on 2009 FDIC and individually collected firm level data covering gross notional, gross positive (negative) fair value and the netted derivatives assets and liabilities for 202 financial firms which includes 20 SIFIs, the bilateral flows are empirically calibrated to reflect data-based constraints. This produces a tiered network with a distinct highly clustered central core of 12 SIFIs that account for 78 percent of all bilateral exposures and a large number of financial intermediaries (FIs) on the periphery. The topology of the network results in the “Too-Interconnected-To-Fail ” (TITF) phenomenon in that the failure of any member of the central tier will bring
Where Is Evolutionary Computation Going? A Temporal Analysis of the EC Community
- GENETIC PROGRAMMING AND EVOLVABLE MACHINES
, 2007
"... Abstract. Studying an evolving complex system and drawing some conclusions from it is an integral part of nature-inspired computing; being a part of that complex system, some insight can also be gained from our knowledge of it. In this paper we study the evolution of the evolutionary computation co- ..."
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Cited by 7 (1 self)
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Abstract. Studying an evolving complex system and drawing some conclusions from it is an integral part of nature-inspired computing; being a part of that complex system, some insight can also be gained from our knowledge of it. In this paper we study the evolution of the evolutionary computation co-authorship network using social network analysis tools, with the aim of extracting some conclusions on its mechanisms. In order to do this, we first examine the evolution of macroscopic properties of the EC co-authorship graph, and then we look at its community structure and its corresponding change along time. The EC network is shown to be in a strongly expansive phase, exhibiting distinctive growth patterns, both at the macroscopic and the mesoscopic level. Keywords: Complex networks, evolutionary computation, social networks analysis 1
Host Centrality in Food Web Networks Determines Parasite Diversity
, 2011
"... Background: Parasites significantly alter topological metrics describing food web structure, yet few studies have explored the relationship between food web topology and parasite diversity. Methods/Principal Findings: This study uses quantitative metrics describing network structure to investigate t ..."
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Cited by 7 (0 self)
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Background: Parasites significantly alter topological metrics describing food web structure, yet few studies have explored the relationship between food web topology and parasite diversity. Methods/Principal Findings: This study uses quantitative metrics describing network structure to investigate the relationship between the topology of the host food web and parasite diversity. Food webs were constructed for four restored brackish marshes that vary in species diversity, time post restoration and levels of parasitism. Our results show that the topology of the food web in each brackish marsh is highly nested, with clusters of generalists forming a distinct modular structure. The most consistent predictors of parasite diversity within a host were: trophic generality, and eigenvector centrality. These metrics indicate that parasites preferentially colonise host species that are highly connected, and within modules of tightly interacting species in the food web network. Conclusions/Significance: These results suggest that highly connected free-living species within the food web may represent stable trophic relationships that allow for the persistence of complex parasite life cycles. Our data demonstrate that the structure of host food webs can have a significant effect on the establishment of parasites, and on the potential for
Extraction and Analysis of Facebook Friendship Relations
"... Online Social Networks (OSNs) are a unique Web and social phenomenon, affecting tastes and behaviors of their users and helping them to maintain/create friendships. It is interesting to analyze the growth and evolution of Online Social Networks both from the point of view of marketing and offer of ..."
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Cited by 6 (2 self)
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Online Social Networks (OSNs) are a unique Web and social phenomenon, affecting tastes and behaviors of their users and helping them to maintain/create friendships. It is interesting to analyze the growth and evolution of Online Social Networks both from the point of view of marketing and offer of new services and from a scientific viewpoint, since their structure and evolution may share similarities with real-life social networks. In social sciences, several techniques for analyzing (offline) social networks have been developed, to evaluate quantitative properties (e.g., defining metrics and measures of structural characteristics of the networks) or qualitative aspects (e.g., studying the attachment model for the network evolution, the binary trust relationships, and the link prediction problem). However, OSN analysis poses novel challenges both to Computer and Social scientists. We present our long-term research effort in analyzing Facebook, the largest and arguably most successful OSN today: it gathers more than 500 million users. Access to data about Facebook users and their friendship relations, is restricted; thus, we acquired the necessary information directly from the front-end of the Web site, in order to reconstruct a sub-graph representing anonymous interconnections among a significant subset of users. We describe our ad-hoc, privacy-compliant crawler for Facebook data extraction. To minimize bias, we adopt two different graph mining techniques: breadth-first search (BFS) and rejection sampling. To analyze the structural properties of samples consisting of millions of nodes, we developed a specific tool for analyzing quantitative and qualitative properties of social networks, adopting and improving existing Social Network Analysis (SNA) techniques and algorithms.
Structural analysis of communities of practice: An investigation of job title, location, and management intention
- Communities and Technologies – Proceedings of the first international conference on Communities and Technologies (C&T 2003
, 2003
"... Abstract. The community of practice phenomenon has been extensively studied in qualitative terms, but there has been relatively little research using quantitative techniques. This study uses the common social network measures of connectedness, density, graph theoretic distance, and core / periphery ..."
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Cited by 6 (0 self)
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Abstract. The community of practice phenomenon has been extensively studied in qualitative terms, but there has been relatively little research using quantitative techniques. This study uses the common social network measures of connectedness, density, graph theoretic distance, and core / periphery fit to examine how groups defined by different characteristics align with community of practice theory. Specifically, it investigates the roles of job title, location, and management intention relative to the structural characteristics of communities of practice. Workers were assigned to groups based upon their job title, job group, division, location, and emergent behavior (results of hierarchical clustering). Initial results suggest that grouping employees by their emergent behavior yields network measures that are most closely related to community of practice theory.
Laggard Clusters as Slow Learners, Emerging Clusters as Locus of Knowledge Cohesion (and Exclusion). A Comparative Study
- in the Wine Industry, LEM Working Paper, Scuola Superiore S. Anna, Pisa Hayek F-A, 1978, New Studies of Philosophy, Politics, Economics and the History of Ideas. London and Henley: Routledge & Kegan
, 2004
"... Abstract: This paper adopts sociometric analysis to explore the process of knowledge acquisition and diffusion in clusters of firms. By comparing the knowledge systems of two clusters selected for being at different stages of their development path, this study shows that the knowledge system of the ..."
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Cited by 6 (0 self)
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Abstract: This paper adopts sociometric analysis to explore the process of knowledge acquisition and diffusion in clusters of firms. By comparing the knowledge systems of two clusters selected for being at different stages of their development path, this study shows that the knowledge system of the laggard cluster is weak, highly disconnected and vulnerable, while in the case of the emerging, dynamic cluster, the knowledge system is characterized by a more connected yet uneven knowledge acquisition and distribution process. These differences are then interpreted considering the heterogeneity of firm knowledge bases across and within clusters and the impact of this latter variable on the degree of intra- and extra-cluster connectivity is explored.
AutoMap User’s Guide 2009
, 2009
"... Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments ..."
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Cited by 6 (2 self)
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Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it
