Can Tweets Predict TV Ratings?

Bridget Sommerdijk, Eric Sanders, Antal van den Bosch


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.
Anthology ID:
L16-1473
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
2965–2970
Language:
URL:
https://aclanthology.org/L16-1473
DOI:
Bibkey:
Cite (ACL):
Bridget Sommerdijk, Eric Sanders, and Antal van den Bosch. 2016. Can Tweets Predict TV Ratings?. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 2965–2970, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Can Tweets Predict TV Ratings? (Sommerdijk et al., LREC 2016)
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PDF:
https://preview.aclanthology.org/update-css-js/L16-1473.pdf