Mapping discursive dynamics of the financial crisis: a structural perspective of concept roles in semantic networks

摘要

Abstract Background/purpose Convenient access to vast and untapped collections of documents generated by organizations is a highly valuable resource for research. These documents (e.g., press releases) are a window into organizational strategies, communication patterns, and organizational behavior. However, the analysis of large document corpora requires appropriate automated methods for text mining and analysis that are able to take into account the redundant and predictable nature of formalized discourse. Methods We use a combination of semantic network analysis and network centrality measures to overcome these particular challenges and to explore the dynamic structural space of concepts in formalized documents pertaining to the recent financial crisis. Data For our analyses, we collect the press releases of the European Central Bank (ECB) and the United States’ Federal Reserve System (Fed) issued between 2006 and 2013 in order to examine their semantic networks before, during, and after the recent financial crisis. Their press releases are notably impactful in their influence on other financial institutions and society at large, especially during times of financial volatility. Results The structural space created from joint centrality metrics reveals salient shifts in the discursive practices of the ECB and Fed. In particular, the Fed exhibits greater attentiveness to the financial crisis especially during the crisis itself, while the ECB’s attention is delayed and increasing steadily. Furthermore, we show both the Fed’s and the ECB’s discourse transitioning into a new “hybrid” state, rather than returning to the pre-crisis status quo. Conclusions Examining the semantic networks of organizational text documents, we find that our analytic approach reveals important discursive shifts, which would not have been discovered under traditional text-analytic approaches. We demonstrate the utility of this approach in investigating large text corpora of organizational discourse, and we anticipate our methods to be comparably valuable in the analysis of a large spectrum of formal and informal discourse.