Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: And the Winner is ...: Bayesian Twitter-based Prediction on 2016 U.S.
  Presidential Election   This paper describes a Naive-Bayesian predictive model for 2016 U.S.
Presidential Election based on Twitter data. We use 33,708 tweets gathered
since December 16, 2015 until February 29, 2016. We introduce a simpler data
preprocessing method to label the data and train the model. The model achieves
95.8% accuracy on 10-fold cross validation and predicts Ted Cruz and Bernie
Sanders as Republican and Democratic nominee respectively. It achieves a
comparable result to those in its competitor methods.

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The categories of this paper are: stat
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The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
30
The categories of this paper are: q-alg
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
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The categories of this paper are: econ
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The categories of this paper are: dg-ga
2
The categories of this paper are: math
25
The categories of this paper are: patt-sol
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The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
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The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin