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Automated Data Collection with R: A Practical Guide to Web Scraping and Text Mining by Dominic Nyhuis, Peter Meissner, Christian Rubba, Simon Munzert

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14 Predicting the 2014 Academy Awards using Twitter

Social media and the social network Twitter, in particular, have attracted the curiosity of scientists from various disciplines. The fact that millions of people regularly interact with the world by tweeting provides invaluable insight into people's feelings, attitudes, and behavior. An increasingly popular approach to make use of this vast amount of public communication is to generate forecasts of various types of events. Twitter data have been used as a prediction tool for elections (Tumasjan et al. 2011), spread of influenza (Broniatowski et al. 2013; Culotta 2010), movie sales (Asur and Huberman 2010), or the stock market (Bollen et al. 2011).

The idea behind these approaches is the “wisdom of the crowds” effect. The aggregated judgment of many people has been shown to frequently be more precise than the judgment of experts or even the smartest person in a group of forecasters (Hogarth 1978). In that sense, if it is possible to infer forecasts from people's tweets, one might expect a fairly accurate forecast of the outcome of an event.

In this case study, we attempt to predict the winners of the 2014 Academy Awards using the tweets in the days prior to the event. Specifically, we try to predict the results of three awards—best picture, best actress, and best actor. A similar effort to ours is proposed by Ghomi et al. (2013). In the next section, we elaborate the data collection by introducing the Twitter APIs and the specific ...

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