Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Wikipedia traffic data and electoral prediction: towards theoretically
  informed models   This aim of this article is to explore the potential use of Wikipedia page
view data for predicting electoral results. Responding to previous critiques of
work using socially generated data to predict elections, which have argued that
these predictions take place without any understanding of the mechanism which
enables them, we first develop a theoretical model which highlights why people
might seek information online at election time, and how this activity might
relate to overall electoral outcomes, focussing especially on how different
types of parties such as new and established parties might generate different
information seeking patterns. We test this model on a novel dataset drawn from
a variety of countries in the 2009 and 2014 European Parliament elections. We
show that while Wikipedia offers little insight into absolute vote outcomes, it
offers a good information about changes in both overall turnout at elections
and in vote share for particular parties. These results are used to enhance
existing theories about the drivers of aggregate patterns in online information
seeking.

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The categories of this paper are: math
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The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: comp-gas
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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-lat