Inferring opinion leadership from digital footprints

Online social networks, being a major part of our daily lives, capture a vast number of digital footprints. With these digital footprints, it is possible to predict highly sensitive personal attributes about individuals - a method Cambridge Analytica exploited for political campaigns. While the idea is intriguing, business research has been rather quiet on this technological development. For this reason, the present article applies the use of digital footprints to an issue of vital importance for managing the diffusion of information: namely, identifying opinion leaders. Traditional approaches to this topic involve cumbersome surveys that are limited in sample size. To uncover a more efficient approach, we examine how opinion leadership, as measured by an established, traditional approach, manifests in users' attributes, as reflected by their digital footprints on Facebook. The study highlights that "what one knows" and "how active one is" are the best predictors for identifying opinion leaders.