From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series
published: June 29, 2010, recorded: May 2010, views: 7674
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
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. consumer conﬁdence and political opinion, and can also pre- dict future movements in the polls. We ﬁnd that temporal smoothing is a critically important issue to support a successful model.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !