Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Do you really follow them? Automatic detection of credulous Twitter
  users   Online Social Media represent a pervasive source of information able to reach
a huge audience. Sadly, recent studies show how online social bots (automated,
often malicious accounts, populating social networks and mimicking genuine
users) are able to amplify the dissemination of (fake) information by orders of
magnitude. Using Twitter as a benchmark, in this work we focus on what we
define credulous users, i.e., human-operated accounts with a high percentage of
bots among their followings. Being more exposed to the harmful activities of
social bots, credulous users may run the risk of being more influenced than
other users; even worse, although unknowingly, they could become spreaders of
misleading information (e.g., by retweeting bots). We design and develop a
supervised classifier to automatically recognize credulous users. The best
tested configuration achieves an accuracy of 93.27% and AUC-ROC of 0.93, thus
leading to positive and encouraging results.

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The categories of this paper are: math
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The categories of this paper are: econ
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The categories of this paper are: hep-ph
20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
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The categories of this paper are: quant-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: alg-geom
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The categories of this paper are: supr-con
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: nucl-th
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The categories of this paper are: gr-qc
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The categories of this paper are: nlin
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The categories of this paper are: astro-ph