부산대학교 도서관

This study demonstrates the use of social media analytics in the context of network television (TV) programs. We first downloaded social media measures for 38 TV programs and their performance ratings over a period of five weeks resulting in a sample size of 165 weekly observations. Specifically we extracted the number of Twitter tweets, followers, followings, Facebook likes, and talk from the official Twitter and Facebook profiles of each TV program. Subsequently we applied OLS Regression techniques and determined that key social media measures positively affect ratings. In essence TV shows with a higher number of Twitter tweets, followers and Facebook talk are likely to associate with higher performance ratings. This study helps TV networks in realizing the pertinence of social media in garnering viewership. Consequently we also propose a social media analytics framework for businesses in identifying brands with higher social media buzz in the objective of improving future economic performance.