From Tweets to Polls : Linking Text Sentiment to Public Opinion Time Series (2010)
| Citations: | 34 - 4 self |
BibTeX
@MISC{Balasubramanyan10fromtweets,
author = {Ramnath Balasubramanyan and Bryan R. Routledge and Noah A. Smith},
title = {From Tweets to Polls : Linking Text Sentiment to Public Opinion Time Series},
year = {2010}
}
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Abstract
We connect measures of public opinion measured from polls with sentiment measured from text. We analyze several surveys on consumer confidence and political opinion over the 2008 to 2009 period, and find they correlate to sentiment word frequencies in contemporaneous Twitter messages. While our results vary across datasets, in several cases the correlations are as high as 80%, and capture important large-scale trends. The results highlight the potential of text streams as a substitute and supplement for traditional polling.
