Investigating the relationship between news characteristics and user reacting, recommending, and commenting
Date:
This study investigates the relationship between news content attributes and user engagement activities. Specifically, we focus on news frame and negative emotion of COVID–19 vaccine stories to examine whether and how the content characteristics influence user reacting, recommending, and commenting behaviors.
Author
Hyo-sun Ryu, Byungjun Kim, Jiseong Yang, and Jae Kook Lee
Abstract
This study investigates the relationship between news content attributes and user engagement activities. Specifically, we focus on news frame and negative emotion of COVID–19 vaccine stories to examine whether and how the content characteristics influence user reacting, recommending, and commenting behaviors. The findings indicate that users are more likely to engage in political and scientific news during health crisis, compared to other types of stories. Furthermore, negativity of news was found to have positive associations with a variety of user engagement activities. Using structural topic modeling and deep learning approach, we analyzed 30,551 news stories and more than 2 million user engagement activities on Naver News, the biggest search engine and news aggregator in South Korea. Implications of the findings are discussed.