Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Community dynamics in connected time-dependent multilayer networks   Different strategies have been considered to extract information from social
media about how similarly people react to the same news or event. In this
context, a powerful method is offered by the application of graph techniques to
the contents produced by social network users. In particular, large events
typically attract enough content traffic along time to enable an analysis that
explicitly models a dependence from the time dimension. Here we demonstrate how
it is possible to extend the application of community detection strategies in
complex networks to the case of time-dependent multilayer networks, whenever
the connection between consecutive time layers is non-trivial. We apply the
method to 400K Twitter post related to the Expo event held in Milan (Italy)
between May and October 2015.

26
The categories of this paper are: bayes-an
4
The categories of this paper are: cond-mat
2
The categories of this paper are: math
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
23
The categories of this paper are: solv-int
10
The categories of this paper are: q-bio
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The categories of this paper are: stat
11
The categories of this paper are: hep-lat
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The categories of this paper are: q-fin
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph