Can Tweets Predict TV Ratings?

Can Tweets Predict TV Ratings? Bridget Sommerdijk, Eric Sanders and Antal van den Bosch Centre for Language Studies / Centre for Language and Speech Technology, Radboud University, the Netherlands {e.sanders, a.vandenbosch}@let.ru.nl Abstract We set out to investigate whether TV ratings and mentions of TV programmes on the Twitter social media platform are correlated. If such a correlation exists, Twitter may be used as an alternative source for estimating viewer popularity. Moreover, the Twitter-based rating estimates may be generated during the programme, or even before. We count the occurrences of programme-specific hashtags in an archive of Dutch tweets of eleven popular TV shows broadcast in the Netherlands in one season, and perform correlation tests. Overall we find a strong correlation of 0.82; the correlation remains strong, 0.79, if tweets are counted a half hour before broadcast time. However, the two most popular TV shows account for most of the positive effect; if we leave out the single and second most popular TV shows, the correlation drops to being moderate to weak. Also, within a TV show, correlations between ratings and tweet counts are mostly weak, while correlations between TV ratings of the previous and next shows are strong. In absence of information on previous shows, Twitter-based counts may be a viable alternative to classic estimation methods for TV ratings. Estimates are more reliable with more popular TV shows. Keywords: Twitter, TV ratings 1. Introduction The social media platform Twitter1 harbors enormous amounts of information, much of which refers to the per- sonal realm. By referring to what one is doing, people pro- vide information that can be used as a basis for research in sociology, demographics, and statistics. In this paper, we focus on TV ratings: how many people watch a certain TV program. Deller et al. (Deller, 2011) explore the rea- sons why it has become popular to use social media, such as Twitter, before and during the watching of TV programs: to suggest others to watch too, from a desire to talk about what they do, and from a desire to be part of a live conver- sation. Our main research question is: can we use Twitter to predict TV ratings? We present a case study focusing on Dutch TV. Similar research questions are discussed by Wakamiya et al. (Wakamiya et al., 2011) who use Twitter to estimate TV ratings based on textual, spatial, and temporal relevance. Oh et al. (Oh et al., 2015) conclude from their study that there is a positive relationship between social media activi- ties and TV ratings. In their study, Sanders and Van den Bosch (Sanders and Van den Bosch, 2013) used a simple method to try to predict the outcome of the political parliamentary elections in the Netherlands in 2012, which worked surprisingly well. By counting the names of political parties and comparing them to polls and actual election results, they achieved a high correlation. Encouraged by this result we set out to apply a similar method to the prediction of TV ratings. …

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