Predicting TV Audience Rating with Social Media Wen-Tai Hsieh Seng-cho T. Chou Institute for Information Industry National Taiwan University
[email protected] [email protected] Yu-Hsuan Cheng Chen-Ming Wu Institute for Information Industry Institute for Information Industry
[email protected] [email protected] more advertising revenues for the television Abstract company. Because these types of social media web- sites, such as Facebook, have already become a part of people’s everyday life, this research will In Taiwan, there are different types of TV pro- try to use the contents generated in the TV pro- grams, and each program usually has its gram fan pages by viewers and the editor (in- broadcast length and frequency. We accumu- cluding Posts, Likes and Comments etc.) and the late the broadcasted TV programs’ word-of- mouth on Facebook and apply the Back- Artificial Neural Network to perform forecasts propagation Network to predict the latest pro- on program ratings. If television companies can gram audience rating. TV audience rating is an find out ratings information in advance, they can important indicator regarding the popularity of use this as a basis to negotiate the advertising programs and it is also a factor to influence the period and fees with advertisers; it can also help revenue of broadcast stations via advertise- the television channel observe the benefits of ments. Currently, the present media environ- operating program fan pages, and then decide ments are drastically changing our media con- whether to reinforce fan page management or sumption patterns. We can watch TV pro- add additional interactions with the fans and fur- grams on YouTube regardless location and ther increase ratings and profits.