Can media forecast technological progress?: A text-mining approach to the on-line newspaper and blog's representation of prospective industrial technologies

摘要

This article critically assesses the utility of both personal blog and mass media (on-line newspaper)’s coverage of future technology in forecasting the prospect of industrial technology. By analyzing the statistical pattern of the South Korean media salience in 13 novel industrial technologies in 2015, the study argues that the mass media is more biased than aggregated blogs in depicting promising new technology. In doing so, the authors present a methodical pathway to address the bias with acceleration and skewness index. The article also applies semantic network analysis for the collected textual data of blogs to represent and interpret people's perspective of industrial technologies. By extracting key concepts from PBS index and merging semantic networks of the 13 technologies, the study derives a key insight that nurturing expertise in the coming era of artificial intelligence and robot would become crucial to integrate key technological competence.