Dynamics of interactions between a traditional news media and its followers

ABSTRACT
The agenda-setting theory in mass communication research studies how news media influence social opinion. In this talk I will show the results of a quantitative study that addresses the agenda-setting problem during the first year of the COVID-19 pandemics by using a large dataset extracted from Twitter and the New York Times (NYT) journal. By combining these two sources, we study the relationship between the agenda set by a traditional news media such as the NYT and the behavior and opinion expressed by its followers in Twitter. We do not fix a specif topic of discussion; instead, we propose a method to automatically extract these topics (or “issues”, in the language of agenda-setting) from the collected data. Then, we propose several measures to characterize issue attention and users’ reaction time. Finally, we compare this behavior against that of the Twitter followers of other US journals and news-sources.

BIO
Mariano Beiró is a Researcher at CONICET and Professor at the Computer Science Department of Universidad de Buenos Aires (Argentina). His research topics cover opinion dynamics, fairness of machine learning algorithms, and human mobility models, from the perspective of social media.