An Exploration of the Potential of Machine Learning Tools for Media Analysis to Support Sense-Making Processes in Foresight - Vignoli, Michela; Rörden, Jan; Wasserbacher, Dana; Kimpeler, Simone (Frontiers in Communication, 2022)
In view of the many discussions about uncertainty regarding the further development of the pandemic and its effects on the economy and society, we explore the hypothesis that Covid-19 has led to an increased presence of individual researchers and experts making forward-looking statements or stating trends in mass media publications. In an explorative approach, we tested if Machine Learning can be applied to identify forward-looking or prognostic statements in contemporary news articles, the persons connected to those statements, and to verify if the statements made match the persons’ expertise, through the use of additional contextual information. The goal was to explore the potential of semi-automated methods already in use for horizon scanning to support sense-making and evaluation processes, in particular for foresight and science communication research. In this paper, we explain the applied method, key results, and discuss limitations, challenges, and opportunities of the proposed approach.