Scholarly ties in innovation and entrepreneurship: a social network perspective
Abstract
Purpose This study examines the patterns of scholarly communication on social media, specifically Twitter (now “X”), among researchers in innovation management and entrepreneurship. The research aims to identify how these communities interact and share knowledge, revealing their similarities and distinctions. It employs social network analysis to uncover novel communication trends within these scholarly fields beyond previous bibliometric evidence. Design/methodology/approach Social network analysis is employed using Twitter data from 2007 to 2023 for 519 highly-cited innovation and entrepreneurship scholars. Louvain and Infomap clustering algorithms are applied to create communication graphs, which are then analyzed to reveal scholars’ interaction patterns. This research takes a comprehensive approach by considering multiple types of interactions (follows, retweets, mentions) to provide a thorough view of the social network. Findings Clustering uncovers six communities of scholars, revealing a well-defined structure in scholarly communications. Although interconnected, a clear distinction can be shown between the communities of innovation management and entrepreneurship on Twitter. Furthermore, 8% of scholars act as bridges between innovation and entrepreneurship, indicating significant interdisciplinary interaction. Originality/value This study contributes to the understanding of how scholars in the fields of innovation management and entrepreneurship communicate and collaborate via social media. By utilizing Twitter-based social network analysis, the research provides a novel perspective on the dynamics of scholarly communication beyond traditional publishing channels. These insights offer practical implications for academic collaboration by identifying bridging scholars and for field development monitoring by revealing how innovation management and entrepreneurship consolidate, fragment and evolve.
// Source
Authors: Jonas Umland, Anne Radunski, Valeska Maul, Robert Rose, Katharina Hölzle
Institutions: Hasso Plattner Institute, Human Factors (Norway), Fraunhofer Institute for Industrial Engineering, Applied Human Factors (United States)