Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Identifying Community Structures in Dynamic Networks   Most real-world social networks are inherently dynamic, composed of
communities that are constantly changing in membership. To track these evolving
communities, we need dynamic community detection techniques. This article
evaluates the performance of a set of game theoretic approaches for identifying
communities in dynamic networks. Our method, D-GT (Dynamic Game Theoretic
community detection), models each network node as a rational agent who
periodically plays a community membership game with its neighbors. During game
play, nodes seek to maximize their local utility by joining or leaving the
communities of network neighbors. The community structure emerges after the
game reaches a Nash equilibrium. Compared to the benchmark community detection
methods, D-GT more accurately predicts the number of communities and finds
community assignments with a higher normalized mutual information, while
retaining a good modularity.

20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
25
The categories of this paper are: patt-sol
8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
34
The categories of this paper are: chem-ph
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
22
The categories of this paper are: chao-dyn