O’Connor, B., Balasubramanyan, R., Routledge, B., & Smith, N. (2010). From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series. In Proceedings of the AAAI Conference on Weblogs and Social Media (pp. 1-8). Washington DC.
https://homes.cs.washington.edu/~nasmith/papers/oconnor+balasubramanyan+routledge+smith. icwsm10.pdf

has been cited by the following article:

• TITLE: Opinion Polls and Statistics Conflict—Time for a Change?

  AUTHORS: Michael D. Nelson

  KEYWORDS: Opinion Poll, Trump, US Election, Statistics, Response Rate

  JOURNAL NAME: Open Journal of Political Science, Vol.9 No.4, October 16, 2019

  ABSTRACT: Generally, in the 2016 United States Presidential Election, Mr. Trump was underestimated by 6.9% and greater than the margin of error. Against this background, the paper discusses the shortcomings of the existing methods and supports the view that a new polling method is needed when related to “opinions”. Graphs show that the maximum error did not occur at the expected value, nor did the data align with a normal statistical bell-shaped distribution. Vulnerabilities exist with combining fact-based statistical analysis with feeling-based opinions. Basic statistics equations do not cover feeling- based factors, i.e. biases, truthfulness, competency, nonresponse rates, etc. A comprehensive pollster accuracy study showed that the most widely used pollsters had significant biases favoring Democrats over Republicans. The 2016 polling failures illustrate deficiencies in the existing approach supporting the view that a new methodology is needed such as Statistical Error Analysis, On-Line Methodology, and others.