Automated News Generation for TV Program Ratings
Soomin Kim, Jong-Hwan Oh, Joonhwan Lee · 2016
Automated journalism, automatically generating stories based on algorithms, has received considerable critical attention in diverse fields. However, automated journalism has not addressed the TV industry in much detail. This research aims to create a system to automatically generate news about TV ratings. The framework will involve undergoing the processes of data gathering, identifying important events by predefined algorithms, generating a story in narrative format, and publishing the output. The algorithm that determines the structure of the stories is defined by analyzing existing news about TV ratings that reflects key variables. Although the output of the research is limited to one type of news template, further attempts could expand to various formats.