• Corpus ID: 11130151

A Game-Theoretic Approach for Detection of Overlapping Communities in Dynamic Complex Networks

@article{Havvaei2016AGA,
  title={A Game-Theoretic Approach for Detection of Overlapping Communities in Dynamic Complex Networks},
  author={Elham Havvaei and Narsingh Deo},
  journal={ArXiv},
  year={2016},
  volume={abs/1603.00509}
}
Complex networks tend to display communities which are groups of nodes cohesively connected among themselves in one group and sparsely connected to the remainder of the network. Detecting such communities is an important computational problem, since it provides an insight into the functionality of networks. Further, investigating community structure in a dynamic network, where the network is subject to change, is even more challenging. This paper presents a game-theoretical technique for… 

Figures and Tables from this paper

A game-theoretic approach for non-overlapping communities detection

Experiments show that the proposed game-theoretic approach is effective to discover non-overlapping communities and obtain high values of modularity and Normalized Mutual Information (NMI) for real-world and synthetic networks in a reasonable time.

A Novel Approach for Community Detection Using the Label Propagation Technique

A new label propagation-based approach to detect community structure in social networks in which a node can obtain labels of different communities, which allows researchers to discover overlapping communities.

Dynamic Trustworthiness Overlapping Community Discovery in Mobile Internet of Things

This paper proposes a detection scheme for dynamic trustworthiness overlapping community, called D2-TOC, which employs evidence-based data between node pairs to construct the trustworthiness relationships between devices and the network model of mobile IoT, which can provide the security guarantee for data interaction from the start.

Odyssey: Creation, Analysis and Detection of Trojan Models

A detector based upon the analysis of intrinsic properties of DNN that could get affected by a Trojan attack is developed; it reveals that Trojan attacks affect the classifier margin and shape of decision boundary around the manifold of the clean data.

Technical Report Column

Quasi-Linear Size Zero Knowledge from Linear-Algebraic PCPs, Eli Ben-Sasson, Alessandro Chiesa, Ariel Gabizon, Madars Virza, TR16-001. Strong ETH Breaks With Merlin and Arthur: Short Non-Interactive

References

SHOWING 1-10 OF 94 REFERENCES

Game Theory and Extremal Optimization for Community Detection in Complex Dynamic Networks

This work proposes a novel approach based on game theory elements and extremal optimization to address dynamic communities detection, formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function.

A game-theoretic framework to identify overlapping communities in social networks

The first time the community detection problem is addressed by a game-theoretic framework that considers community formation as the result of individual agents’ rational behaviors, and the algorithm is effective in identifying overlapping communities.

Finding and evaluating community structure in networks.

  • M. NewmanM. Girvan
  • Computer Science
    Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2004
It is demonstrated that the algorithms proposed are highly effective at discovering community structure in both computer-generated and real-world network data, and can be used to shed light on the sometimes dauntingly complex structure of networked systems.

Adaptive algorithms for detecting community structure in dynamic social networks

This paper presents Quick Community Adaptation (QCA), an adaptive modularity-based method for identifying and tracing community structure of dynamic online social networks and demonstrates the bright applicability of the algorithm via a realistic application on routing strategies in MANETs.

A Game Theoretic Framework for Community Detection

This work treats each node as a player in a hedonic game and focus on their ability to form fair and stable community structures in the context of global optimization.

Finding community structure in very large networks.

A hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with n vertices and m edges is O (md log n) where d is the depth of the dendrogram describing the community structure.

Defining and identifying communities in networks.

This article proposes a local algorithm to detect communities which outperforms the existing algorithms with respect to computational cost, keeping the same level of reliability and applies to a network of scientific collaborations, which, for its size, cannot be attacked with the usual methods.

Overlapping community detection at scale: a nonnegative matrix factorization approach

This paper presents BIGCLAM (Cluster Affiliation Model for Big Networks), an overlapping community detection method that scales to large networks of millions of nodes and edges and builds on a novel observation that overlaps between communities are densely connected.

Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities.

The basic ideas behind the previous benchmark are extended to generate directed and weighted networks with built-in community structure, and the possibility that nodes belong to more communities is considered, a feature occurring in real systems, such as social networks.

Community detection in graphs

...