Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Robust Naive Learning in Social Networks   We study a model of opinion exchange in social networks where a state of the
world is realized and every agent receives a zero-mean noisy signal of the
realized state. It is known from Golub and Jackson that under the DeGroot
dynamics agents reach a consensus which is close to the state of the world when
the network is large. The DeGroot dynamics, however, is highly non-robust and
the presence of a single `bot' that does not adhere to the updating rule, can
sway the public consensus to any other value. We introduce a variant of the
DeGroot dynamics which we call \emph{ $\varepsilon$-DeGroot}. The
$\varepsilon$-DeGroot dynamics approximates the standard DeGroot dynamics and
like the DeGroot dynamics it is Markovian and stationary. We show that in
contrast to the standard DeGroot dynamics, the $\varepsilon$-DeGroot dynamics
is highly robust both to the presence of bots and to certain types of
misspecifications.

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The categories of this paper are: alg-geom
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th
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The categories of this paper are: q-fin
16
The categories of this paper are: stat
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
22
The categories of this paper are: chao-dyn
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
7
The categories of this paper are: hep-th
9
The categories of this paper are: nlin
21
The categories of this paper are: adap-org