• Corpus ID: 18048854

Election Bias: Comparing Polls and Twitter in the 2016 U.S. Election

  title={Election Bias: Comparing Polls and Twitter in the 2016 U.S. Election},
  author={David Anuta and Josh Churchin and Jiebo Luo},
While the polls have been the most trusted source for election predictions for decades, in the recent presidential election they were called inaccurate and biased. How inaccurate were the polls in this election and can social media beat the polls as an accurate election predictor? Polls from several news outlets and sentiment analysis on Twitter data were used, in conjunction with the results of the election, to answer this question and outline further research on the best method for predicting… 

Exploring the Effectiveness of Twitter at Polling the United States 2016 Presidential Election

The results show that when using tweet sentiment, the results obtain similar margins to polls conducted during the election period and come close to the actual popular vote outcome.

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This work creates a dataset consisting of approximately 3 million tweets ranging from September 22nd to November 8th, 2016 to explore the effectiveness of social media as a resource for both polling and predicting the election outcome.

A Longitudinal Study on Twitter-Based Forecasting of Five Dutch National Elections

An eight-year longitudinal study of predicting the outcome of elections based on party mentions in tweets found reasonably accurate predictions can be obtained that are under twice the error of the classic polls, but only after post-hoc optimization.

Location-Based Twitter Sentiment Analysis for Predicting the U.S. 2016 Presidential Election

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One of the key findings of this study is recognizing that negative or positive polarities in the tweets is not a good indicator to determine support for this candidate.

Prediction of USA November 2020 Election Results Using Multifactor Twitter Data Analysis Method

A new multifactor model for the election result prediction based on Twitter data has been developed and tested by attempting to predict the results of the US 2020 elections in November, which had not yet taken place when the first version of this article was written.



Predicting US Primary Elections with Twitter

Using social media for political analysis is becoming a common practice, especially during election time. Many researchers and media are trying to use social media to understand the public opinion

From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series

This work connects measures of public opinion measured from polls with sentiment measured from text, and finds that temporal smoothing is a critically important issue to support a suc- cessful model.

Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment

It is found that the mere number of messages mentioning a party reflects the election result, and joint mentions of two parties are in line with real world political ties and coalitions.

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