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Article citations


Huang, Y.Y., Yen, Y. A., Ku, T.W. and Lin, S.D. (2014) A Weight-Sharing Gaussian Process Model Using Web-Based Information for Audience Rating Prediction. Technologies and Applications of Artificial Intelligence Lecture Notes in Computer Science, 19th International Conference, TAAI 1014, Taipei, 21-23 November 2014, 198-208.

has been cited by the following article:

  • TITLE: Television Meets Facebook: The Correlation between TV Ratings and Social Media

    AUTHORS: Mei-Hua Cheng, Yi-Chen Wu, Ming-Chih Chen

    KEYWORDS: Social Media, TV Ratings, Facebook, Audience Measurement

    JOURNAL NAME: American Journal of Industrial and Business Management, Vol.6 No.3, March 25, 2016

    ABSTRACT: This study examines the relationship between social media site Facebook and TV ratings drawing from audience factors of integration model of audience behavior. Based on context of Taiwan television network programs, this study collected measures for Facebook likes, shares, comments, posts for three genres of television shows and their Nielsen ratings over a period of eleven weeks, resulting in the size of sample more than 130 observations. This study applied multiple regression models and determined that the key social media measures correlate with TV ratings. In essence, TV shows with higher number of posts and engagement are likely to relate to higher ratings, special in drama shows. Subsequently, this study constructed the TV prediction models with measures for Facebook via SVR. The results suggested that prediction models are a good forecasting of which MAPE was between 10% - 20%, even less than 10%. This implies that TV network should be motivated to invest in social media and engage their audience and analysts can use social media as a mechanism of exante forecasting.