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LREC 2016main

Can Tweets Predict TV Ratings?

Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)

DOI:10.63317/4qdyw3yk8p3a

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.

Details

Paper ID
lrec2016-main-473
Pages
pp. 2965-2970
BibKey
sommerdijk-etal-2016-tweets
Editors
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asunción Moreno, Jan Odijk, Stelios Piperidis
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
978-2-9517408-9-1
Conference
Tenth International Conference on Language Resources and Evaluation
Location
Portorož, Slovenia
Date
23 - 28 May 2016

Authors

  • BS

    Bridget Sommerdijk

  • ES

    Eric Sanders

  • Av

    Antal van den Bosch

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