Detecting communities is Hard (And Counting Them is Even Harder)

Author Aviad Rubinstein



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Aviad Rubinstein

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Aviad Rubinstein. Detecting communities is Hard (And Counting Them is Even Harder). In 8th Innovations in Theoretical Computer Science Conference (ITCS 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 67, pp. 42:1-42:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017) https://doi.org/10.4230/LIPIcs.ITCS.2017.42

Abstract

We consider the algorithmic problem of community detection in networks. Given an undirected friendship graph G, a subset
S of vertices is an (a,b)-community if: * Every member of the community is friends with an (a)-fraction of the community; and
* every non-member is friends with at most a (b)-fraction of the
community. 

[Arora, Ge, Sachdeva, Schoenebeck 2012] gave a quasi-polynomial
time algorithm for enumerating all the (a,b)-communities
for any constants a>b. 

Here, we prove that, assuming the Exponential Time Hypothesis (ETH),
quasi-polynomial time is in fact necessary - and even for a much weaker
approximation desideratum. Namely, distinguishing between:
* G contains an (1,o(1))-community; and
* G does not contain a (b,b+o(1))-community
for any b.

We also prove that counting the number of (1,o(1))-communities
requires quasi-polynomial time assuming the weaker #ETH.

Subject Classification

Keywords
  • Community detection
  • stable communities
  • quasipolynomial time

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