<p>There's a recent paper [1] on dense subgraph (i.e. community) detection in the context of distributed computing. 
In [1], each node of the graph represents an operating entity (i.e. runs an instance of a distributed algorithm) and each node can communicate with its neighboring nodes by sending messages. The graph itself can change (slowly) over time. Note that the connections in social networks evolve over time, so considering a dynamic graph seems like the right model.
By running a distributed algorithm, each node can locally determine whether it's part of a dense subgraph. You might want to consult the related work section of [1] to get pointers to other references.</p>

<p>[1] Atish Das Sarma, Ashwin Lall, Danupon Nanongkai, Amitabh Trehan: Dense Subgraphs on Dynamic Networks. DISC 2012: 151-165. Full paper available at <a href="http://arxiv.org/abs/1208.1454" rel="nofollow">http://arxiv.org/abs/1208.1454</a></p>

CC BY-SA 3.0
2014-12-05T03:09:27.070Z
2014-12-05T03:09:27.070Z
Peter
<p>Is anyone aware of the must read papers to get knowledge of the most recent algorithms and method for community detection in graphs, especially those that represent social networks?</p>

CC BY-SA 3.0
2014-12-04T23:33:38.273Z
Girvan-Newman algorithm is a well-known algorithm and appeared in many research papers. You can find it in Wiki.
Bangye
CC BY-SA 3.0
2014-12-05T17:51:45.663Z
Newman's Q-modularity also seems popular. But I think this question is problematic: on one hand, the literature on community discovery is quite large. On the other, while there is some overlap with theory, this is not really a theory question until you define "community" more precisely.
Sasho Nikolov
<graph-theory><graph-algorithms><big-list><dc.distributed-comp><social-sciences>
State of the art algorithms for community detection in graphs
Magellanea
# State of the art algorithms for community detection in graphs

(Asked by: username_0 on 2014-12-04)

Is anyone aware of the must read papers to get knowledge of the most recent algorithms and method for community detection in graphs, especially those that represent social networks?

**Tags:** graph-theory, graph-algorithms, big-list, dc.distributed-comp, social-sciences
> **Comments:**
> **username_1**: Girvan-Newman algorithm is a well-known algorithm and appeared in many research papers. You can find it in Wiki.  
> **username_2**: Newman's Q-modularity also seems popular. But I think this question is problematic: on one hand, the literature on community discovery is quite large. On the other, while there is some overlap with theory, this is not really a theory question until you define "community" more precisely.  

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## 1 answers

### Answer by username_3 on 2014-12-05. Score: 1

There's a recent paper [1] on dense subgraph (i.e. community) detection in the context of distributed computing.
In [1], each node of the graph represents an operating entity (i.e. runs an instance of a distributed algorithm) and each node can communicate with its neighboring nodes by sending messages. The graph itself can change (slowly) over time. Note that the connections in social networks evolve over time, so considering a dynamic graph seems like the right model.
By running a distributed algorithm, each node can locally determine whether it's part of a dense subgraph. You might want to consult the related work section of [1] to get pointers to other references.

[1] Atish Das Sarma, Ashwin Lall, Danupon Nanongkai, Amitabh Trehan: Dense Subgraphs on Dynamic Networks. DISC 2012: 151-165. Full paper available at <http://arxiv.org/abs/1208.1454>


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