Statistical mechanics of community detection

Reichardt, J.; Bornholdt, Stefan

doi:10.1103/physreve.74.016110

Cited by 1,713 publications

(1,684 citation statements)

References 30 publications

Supporting

Mentioning

1,603

Contrasting

Unclassified

Order By: Relevance

“…The goal of such algorithms is to find clusters with strong connectivity and group them together. While a number of different algorithms exist, we used one which uses spin glass quality function from magnetic systems and modularity optimization in its computation 52 .…”

Section: Social Metricsmentioning

confidence: 99%

Social networks reveal cultural behaviour in tool-using dolphins

et al. 2012

View full text Add to dashboard Cite

Animal tool use is of inherent interest given its relationship to intelligence, innovation and cultural behaviour. Here we investigate whether shark Bay bottlenose dolphins that use marine sponges as hunting tools (spongers) are culturally distinct from other dolphins in the population based on the criteria that sponging is both socially learned and distinguishes between groups. We use social network analysis to determine social preferences among 36 spongers and 69 non-spongers sampled over a 22-year period while controlling for location, sex and matrilineal relatedness. Homophily (the tendency to associate with similar others) based on tool-using status was evident in every analysis, although maternal kinship, sex and location also contributed to social preference. Female spongers were more cliquish and preferentially associated with other spongers over non-spongers. Like humans who preferentially associate with others who share their subculture, tool-using dolphins prefer others like themselves, strongly suggesting that sponge tool-use is a cultural behaviour.

show abstract

Section: Social Metricsmentioning

confidence: 99%

Social networks reveal cultural behaviour in tool-using dolphins

et al. 2012

View full text Add to dashboard Cite

show abstract

“…We used the spin-glass algorithm, which tests for communities in the network whereby the number and weighted strength of edges within a cluster exceed the number and weighted strength of edges between nodes in another cluster (Reichardt & Bornholdt, 2006). We applied the spin-glass community function of the R package igraph over the glasso network (weights = null, vertex = null, parupdate = false, gamma = 0.5, start temperature = 1, stop temperature = 0.01, cooling factor = 0.99, spins = 17) (Csardi & Nepusz, 2006).…”

Section: Methodsmentioning

confidence: 99%

Making connections: exploring the centrality of posttraumatic stress symptoms and covariates after a terrorist attack

Birkeland

Heir

2017

European Journal of Psychotraumatology

View full text Add to dashboard Cite

Background: Posttraumatic stress symptoms are interconnected. Knowledge about which symptoms of posttraumatic stress are more strongly interconnected or central than others may have implications for the targeting of clinical interventions. Exploring whether symptoms of posttraumatic stress may be differentially related to covariates can contribute to our knowledge on how posttraumatic stress symptoms arise and are maintained. Objective: This study aimed to identify the most central symptoms of posttraumatic stress and their interconnections, and to explore how covariates such as exposure, sex, neuroticism, and social support are related to the network of symptoms of posttraumatic stress. Method: This study used survey data from ministerial employees collected approximately 10 months after the 2011 Oslo bombing that targeted the governmental quarters (n = 190). We conducted network analyses using Gaussian graphical models and the lasso regularization. Results: The network analysis revealed reliably strong connections between intrusive thoughts and nightmares, feeling easily startled and overly alert, and between feeling detached and emotionally numb. The most central symptom in the symptom network was feeling emotionally numb. The covariates were generally not found to have high centrality in the symptom network. An exception was that being female was connected to a high physiological reactivity to reminders of the trauma. Conclusions: Ten months after a workplace terror attack emotional numbness appears to be of high centrality in the symptom network of posttraumatic stress. Fear circuitry and dysphoric symptoms may constitute two functional entities in chronic posttraumatic stress. Clinical interventions targeting numbness may be beneficial in the treatment of posttraumatic stress, at least after workplace terrorism.

show abstract

“…Specifically, we need to establish whether all psychological networks can be validly conceptualized as "spinglasses" (i.e., extensions of Ising models; Reichardt & Bornholdt, 2006). More generally, we need to establish whether we can use the structural topography of a network (i.e., the constellation and weight of edges between nodes) to infer community structure validly in psychological networks.…”

Section: Discussion and Next Stepsmentioning

confidence: 99%

“…One such method is the spinglass community detection algorithm. The spinglass algorithm uses simulations based on the Potts-model from statistical mechanics (Reichardt & Bornholdt, 2006). Due to the simulations, the algorithm is non-deterministic.…”

mentioning

confidence: 99%

The ComDet Package - Iterated Community Detection for the Analysis of Community Membership, its Stability and the Detection of Fuzzy Community Boundaries.

M.Werner¹

2018

Preprint

View full text Add to dashboard Cite

In recent years, network analysis has entered psychological science. In psychological network models, nodes are variables and edges are estimated relationships between these variables. In this project, we answer recent calls for the use of established network community detection algorithms to detect clusters in psychological networks. This technical note introduces the ComDet package (under development for use in R), a package aimed at extending the functionality of the commonly used non-deterministic community detection algorithm spinglass. ComDet repeatedly performs the spinglass community detection algorithm (based on the igraph package in R) for a specified number of runs, quantifies and summarizes the results across runs, and visualizes those results. Our extended community detection function builds upon the prior literature in two ways. First, it offers summarizing output that communicates the stability and variability of particular community results. Second, because this package is implemented in R, the same platform commonly used to assess psychological networks, it can be readily applied as part of the growing toolbox for assessing psychological networks. This technical note will be updated with new insights in the near future. The final aim of this project is to provide researchers with a freely available R-package that runs the ComDet function using spinglass and, potentially, other non-deterministic community detection algorithms.

show abstract

Statistical mechanics of community detection

Cited by 1,713 publications

References 30 publications

Social networks reveal cultural behaviour in tool-using dolphins

Social networks reveal cultural behaviour in tool-using dolphins

Making connections: exploring the centrality of posttraumatic stress symptoms and covariates after a terrorist attack

The ComDet Package - Iterated Community Detection for the Analysis of Community Membership, its Stability and the Detection of Fuzzy Community Boundaries.

Contact Info

Product

Resources

About