2,508 research outputs found
Modularity and community detection in bipartite networks
The modularity of a network quantifies the extent, relative to a null model
network, to which vertices cluster into community groups. We define a null
model appropriate for bipartite networks, and use it to define a bipartite
modularity. The bipartite modularity is presented in terms of a modularity
matrix B; some key properties of the eigenspectrum of B are identified and used
to describe an algorithm for identifying modules in bipartite networks. The
algorithm is based on the idea that the modules in the two parts of the network
are dependent, with each part mutually being used to induce the vertices for
the other part into the modules. We apply the algorithm to real-world network
data, showing that the algorithm successfully identifies the modular structure
of bipartite networks.Comment: RevTex 4, 11 pages, 3 figures, 1 table; modest extensions to conten
Trainâtheâtrainer: Methodology to learn the cognitive interview
Research has indicated that police may not receive enough training in interviewing cooperative witnesses, specifically in use of the cognitive interview (CI). Practically, for the CI to be effective in realâworld investigations, police investigators must be trained by law enforcement trainers. We conducted a threeâphase experiment to examine the feasibility of training experienced law enforcement trainers who would then train others to conduct the CI. We instructed Federal Bureau of Investigation and local law enforcement trainers about the CI (Phase I); law enforcement trainers from both agencies (n = 4, 100% male, mean age = 50 years) instructed university students (n = 25, 59% female, mean age = 21 years) to conduct either the CI or a standard law enforcement interview (Phase II); the student interviewers then interviewed other student witnesses (n = 50, 73% female, mean age = 22 years), who had watched a simulated crime (phase III). Compared with standard training, interviews conducted by those trained by CIâtrained instructors contained more information and at a higher accuracy rate and with fewer suggestive questions.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147804/1/jip1518_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147804/2/jip1518.pd
The Peculiar Phase Structure of Random Graph Bisection
The mincut graph bisection problem involves partitioning the n vertices of a
graph into disjoint subsets, each containing exactly n/2 vertices, while
minimizing the number of "cut" edges with an endpoint in each subset. When
considered over sparse random graphs, the phase structure of the graph
bisection problem displays certain familiar properties, but also some
surprises. It is known that when the mean degree is below the critical value of
2 log 2, the cutsize is zero with high probability. We study how the minimum
cutsize increases with mean degree above this critical threshold, finding a new
analytical upper bound that improves considerably upon previous bounds.
Combined with recent results on expander graphs, our bound suggests the unusual
scenario that random graph bisection is replica symmetric up to and beyond the
critical threshold, with a replica symmetry breaking transition possibly taking
place above the threshold. An intriguing algorithmic consequence is that
although the problem is NP-hard, we can find near-optimal cutsizes (whose ratio
to the optimal value approaches 1 asymptotically) in polynomial time for
typical instances near the phase transition.Comment: substantially revised section 2, changed figures 3, 4 and 6, made
minor stylistic changes and added reference
Researching the use of force: The background to the international project
This article provides the background to an international project on use of force by the police that was carried out in eight countries. Force is often considered to be the defining characteristic of policing and much research has been conducted on the determinants, prevalence and control of the use of force, particularly in the United States. However, little work has looked at police officersâ own views on the use of force, in particular the way in which they justify it. Using a hypothetical encounter developed for this project, researchers in each country conducted focus groups with police officers in which they were encouraged to talk about the use of force. The results show interesting similarities and differences across countries and demonstrate the value of using this kind of research focus and methodology
Tropical tele-connections to the Mediterranean climate and weather
Some strong natural fluctuations of climate in the Eastern Mediterranean (EM) region are shown to be connected to the major tropical systems. Potential relations between EM rainfall extremes to tropical systems, e.g. El Niño, Indian Monsoon and hurricanes, are demonstrated. For a specific event, high resolution modelling of the severe flood on 3-5 December 2001 in Israel suggests a relation to hurricane Olga. In order to understand the factors governing the EM climate variability in the summer season, the relationship between extreme summer temperatures and the Indian Monsoon was examined. Other tropical factors like the Red-Sea Trough system and the Saharan dust are also likely to contribute to the EM climate variability
Finding community structure in networks using the eigenvectors of matrices
We consider the problem of detecting communities or modules in networks,
groups of vertices with a higher-than-average density of edges connecting them.
Previous work indicates that a robust approach to this problem is the
maximization of the benefit function known as "modularity" over possible
divisions of a network. Here we show that this maximization process can be
written in terms of the eigenspectrum of a matrix we call the modularity
matrix, which plays a role in community detection similar to that played by the
graph Laplacian in graph partitioning calculations. This result leads us to a
number of possible algorithms for detecting community structure, as well as
several other results, including a spectral measure of bipartite structure in
networks and a new centrality measure that identifies those vertices that
occupy central positions within the communities to which they belong. The
algorithms and measures proposed are illustrated with applications to a variety
of real-world complex networks.Comment: 22 pages, 8 figures, minor corrections in this versio
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