[We’re pleased to welcome author Michael Etter of the City University of London, UK. Etter recently published an article in Business & Society entitled “Measuring Organizational Legitimacy in Social Media: Assessing Citizens’ Judgments With Sentiment Analysis,” co-authored by Elanor Colleoni, Laura Illia, Katia Meggiorin, and Antonino D’Eugenio. From Etter:]
Social media have given ordinary citizens the opportunity to freely express their opinions and feelings in any tone or style. The heated discussions around various topics from politics, sports, and corporations often evolve in parallel to news media coverage. Accordingly, we have developed the idea that a measurement of citizens’ judgment in social media can give researchers a new way to assess the legitimacy of organizations. Compared to existing measurements that, for example, assess judgments in news media coverage, a measurement based on social media would directly access the voices of ordinary citizens and therefore account for their heterogeneous norms and expectations.
In this article we describe and test how a measurement based on social media data can give indication for organizational legitimacy. We use the method of sentiment analysis that is based on computational linguistics and apply it to a case from the banking industry over a one year period.
Our findings show that, indeed, an analysis of 14’000 tweets reveals a different judgment than the analysis of 730 news articles. Compared to the news media, citizens judge the bank in a much more negative way. Also we find that the bank is discussed by 6000 citizens and for a broad variety of topics (around 400 hashtags). Clearly, social media data gives researchers access to different judgments than found in news media, which are written by a few journalists that adhere to professional norms and standards and are subject to various selection processes. We therefore encourage researchers to take into account social media, such as Twitter, in order to achieve a richer understanding of legitimation processes in a digital world. For practitioners, sentiment analysis of twitter data is a tool to monitor and identify issues and sentiment in a timely manner.
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