Text Mining and Dimension Reduction Methods of Exploring Isomorphism in Corporate Communication

This study analyzes the isomorphism pressures within the context of sustainability by exploring Twitter communication in the energy sector. Social Media, in particular Twitter, provide a new opportunity to explore the linguistic dimension in corporate communications. This paper proposes the use of Social Medja linguistic data (tweets; including hashtags and keywords) and a triangulated method (text mining, web mining, linguistic and content analysis) to examine trends in tweets for individual companies. Based on the institutional theory of organizational communication, this study examines the relationship between the concept of sustainability and isomorphism, the latter of which leads to the adoption of similar models and attitudes among organizations. lt applies text mining and correspondence methods within R software for energy sector tweets in English from 2016. The results reveal a tendency among energy companies to follow similar patterns in Twitter communication on sustainability. This provides insight into the mechanisms that lead to isomorphism in organizational communication.