Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Quantifying discrepancies in opinion spectra from online and offline
  networks   Online social media such as Twitter are widely used for mining public
opinions and sentiments on various issues and topics. The sheer volume of the
data generated and the eager adoption by the online-savvy public are helping to
raise the profile of online media as a convenient source of news and public
opinions on social and political issues as well. Due to the uncontrollable
biases in the population who heavily use the media, however, it is often
difficult to measure how accurately the online sphere reflects the offline
world at large, undermining the usefulness of online media. One way of
identifying and overcoming the online-offline discrepancies is to apply a
common analytical and modeling framework to comparable data sets from online
and offline sources and cross-analyzing the patterns found therein. In this
paper we study the political spectra constructed from Twitter and from
legislators' voting records as an example to demonstrate the potential limits
of online media as the source for accurate public opinion mining.

18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph
0
The categories of this paper are: hep-ph
9
The categories of this paper are: nlin
22
The categories of this paper are: chao-dyn
34
The categories of this paper are: chem-ph
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
2
The categories of this paper are: math
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio