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Journal articleClough JR, Gollings J, Loach TV, et al., 2015,
Transitive reduction of citation networks
, Journal of Complex Networks, Vol: 3, Pages: 189-203, ISSN: 2051-1310In many complex networks, the vertices are ordered in time, and edges represent causal connections. We propose methods of analysing such directed acyclic graphs taking into account the constraints of causality and highlighting the causal structure. We illustrate our approach using citation networks formed from academic papers, patents and US Supreme Court verdicts. We show how transitive reduction (TR) reveals fundamental differences in the citation practices of different areas, how it highlights particularly interesting work, and how it can correct for the effect that the age of a document has on its citation count. Finally, we transitively reduce null models of citation networks with similar degree distributions and show the difference in degree distributions after TR to illustrate the lack of causal structure in such models.
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Journal articleMcAteer RTJ, Aschwanden MJ, Dimitropoulou M, et al., 2015,
25 Years of self-organized criticality: numerical detection methods
, Space Science Reviews, Vol: 198, Pages: 217-266, ISSN: 1572-9672The detection and characterization of self-organized criticality (SOC), in bothreal and simulated data, has undergone many significant revisions over the past 25 years. The explosive advances in the many numerical methods available for detecting, discriminating, and ultimately testing, SOC have played a critical role in developing our understanding of how systems experience and exhibit SOC. In this article, methods of detecting SOC are reviewed; from correlations to complexity to critical quantities. A description of the basicautocorrelation method leads into a detailed analysis of application-oriented methods developed in the last 25 years. In the second half of this manuscript space-based, time-based and spatial-temporal methods are reviewed and the prevalence of power laws in nature is described, with an emphasis on event detection and characterization. The search for numericalmethods to clearly and unambiguously detect SOC in data often leads us outside the comfort zone of our own disciplines—the answers to these questions are often obtained by studying the advances made in other fields of study. In addition, numerical detection methods often provide the optimum link between simulations and experiments in scientific research. We seek to explore this boundary where the rubber meets the road, to review this expandingfield of research of numerical detection of SOC systems over the past 25 years, and to iterate forwards so as to provide some foresight and guidance into developing breakthroughs in this subject over the next quarter of a century.
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Journal articleFont-Clos F, Pruessner G, Moloney NR, et al., 2015,
The perils of thresholding
, New Journal of Physics, Vol: 17, ISSN: 1367-2630The thresholding of time series of activity or intensity is frequently used to define and differentiateevents. This is either implicit, for example due to resolution limits, or explicit, in order to filter certainsmall scale physics from the supposed true asymptotic events. Thresholding the birth–death process,however, introduces a scaling region into the event size distribution, which is characterized by anexponent that is unrelated to the actual asymptote and is rather an artefact of thresholding. As a result,numerical fits of simulation data produce a range of exponents, with the true asymptote visible only inthe tail of the distribution. This tail is increasingly difficult to sample as the threshold is increased. Inthe present case, the exponents and the spurious nature of the scaling region can be determinedanalytically, thus demonstrating the way in which thresholding conceals the true asymptote. Theanalysis also suggests a procedure for detecting the influence of the threshold by means of a datacollapse involving the threshold-imposed scale.
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Journal articleKawamoto H, Takayasu H, Jensen HJ, et al., 2015,
Precise calculation of a bond percolation transition and survival rates of nodes in a complex network
, PLOS One, Vol: 10, ISSN: 1932-6203Through precise numerical analysis, we reveal a new type of universal loopless percolation transition in randomly removed complex networks. As an example of a real-world network, we apply our analysis to a business relation network consisting of approximately 3,000,000 links among 300,000 firms and observe the transition with critical exponents close to the mean-field values taking into account the finite size effect. We focus on the largest cluster at the critical point, and introduce survival probability as a new measure characterizing the robustness of each node. We also discuss the relation between survival probability and k-shell decomposition.
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Journal articleLoe CW, Jensen HJ, 2015,
Comparison of communities detection algorithms for multiplex
, Physica A - Statistical Mechanics and Its Applications, Vol: 431, Pages: 29-45, ISSN: 0378-4371Multiplex is a set of graphs on the same vertex set, i.e. {G(V,E1),…,G(V,Em)}{G(V,E1),…,G(V,Em)}. It is a type of generalized graph to model the multiple relationships in a system with parallel edges between vertices. An important application in Network Science is to capture community structures in multiplex as a way to modularize the system. This paper is a literature review and comparative analysis on the existing communities detection algorithms for multiplex. The conclusion is that many of the algorithms deviate in the concept of multi-relational communities and the wrong choice of algorithm can deviate one from his intended concept.
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Journal articleMassobrio P, de Arcangelis L, Pasquale V, et al., 2015,
Criticality as a signature of healthy neural systems
, Frontiers in Systems Neuroscience, Vol: 9, ISSN: 1662-5137 -
Conference paperLoach TV, Evans TS, 2015,
Ranking Journals Using Altmetrics
, 15th International Conference of the International-Society-for-Scientometrics-and-Informetrics (ISSI) on Scientometrics and Informetrics, Publisher: INT SOC SCIENTOMETRICS & INFORMETRICS-ISSI, Pages: 89-94, ISSN: 2175-1935- Author Web Link
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Conference paperClough JR, Evans TS, 2015,
Time & Citation Networks
, 15th International Conference of the International-Society-for-Scientometrics-and-Informetrics (ISSI) on Scientometrics and Informetrics, Publisher: INT SOC SCIENTOMETRICS & INFORMETRICS-ISSI, Pages: 1073-1078, ISSN: 2175-1935 -
Conference paperPiovani D, Grujic J, Jensen HJ, 2015,
Forecasting systemic transitions in high dimensional stochastic complex systems
, 4th International Conference on Mathematical Modeling in Physical Sciences (IC-MSquare), Publisher: IOP PUBLISHING LTD, ISSN: 1742-6588 -
Conference paperGoldberg SR, Anthony H, Evans TS, 2015,
Do We Need Global and Local Knowledge of the Citation Network?
, 15th International Conference of the International-Society-for-Scientometrics-and-Informetrics (ISSI) on Scientometrics and Informetrics, Publisher: INT SOC SCIENTOMETRICS & INFORMETRICS-ISSI, Pages: 282-283, ISSN: 2175-1935
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