Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: R\^ole communautaire des capitalistes sociaux dans Twitter   Les capitalistes sociaux sont des utilisateurs de m\'edias sociaux tels que
Twitter, appliquant diverses techniques pour obtenir un maximum de
visibilit\'e. Ils peuvent \^etre n\'efastes \`a l'\'equilibre du service, dans
la mesure o\`u leurs comptes, en gagnant en importance sans r\'eelle raison de
contenu, rendent difficile l'acc\`es \`a un contenu pertinent. Dans ce travail,
nous nous int\'eressons \`a leur caract\'erisation d'un point de vue purement
topologique, i.e. sans consid\'erer la nature des contenus partag\'es. Nous
utilisons pour cela la notion de r\^ole communautaire, qui est bas\'ee sur la
structure de communaut\'es du r\'eseau \'etudi\'e. Nous apportons des
modifications \`a des mesures pr\'ec\'edemment d\'efinies \`a cet effet, et
proposons une m\'ethode objective de d\'etection des r\^oles. Nous appliquons
ensuite notre m\'ethode \`a l'analyse d'un r\'eseau repr\'esentant Twitter. Nos
r\'esultats montrent que les r\^oles que nous identifions via nos mesures se
r\'ev\`elent particuli\`erement coh\'erents par rapport aux capitalistes
sociaux du r\'eseau Twitter, dont le comportement est clairement
identifi\'e---Social capitalists are social media users taking advantage of
various methods to maximize their visibility. This results in artificially
important accounts, in the sense this importance is not backed by any real
content. The risk is then to see those accounts hiding relevant contents and
therefore preventing other users to access them. In this work, we want to
characterize social capitalists from a purely topological perspective, i.e.
without considering the nature of the shared contents. For this purpose, we use
the notion of community role, based on the community structure of the studied
network. We modify some measures previously designed for this matter, and
propose an objective method to determine roles. We then apply this method to
the analysis of a Twitter network. Our results show the roles identified
through our measures are particularly consistent with Twitter's social
capitalists, whose behavior was clearly identified.

20
The categories of this paper are: acc-phys
16
The categories of this paper are: stat
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
33
The categories of this paper are: plasm-ph
7
The categories of this paper are: hep-th
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The categories of this paper are: funct-an
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The categories of this paper are: nucl-ex
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The categories of this paper are: solv-int