Discourse-centric Perspectives of Emerging Technology Diffusion: The Case of Blockchain
Meaning has been a central concept to account for why some technologies are adopted widely while others are not. While the dominant paradigm has been an economic-rationalistic approach, many studies began to explain that the spread of emerging technologies is often shaped by the discourses or meanings, which facilitate the interpretation and legitimation of the given technology.
In this study, I used longitudinal news data published from 2013 to 2020 to investigate how blockchain has become accepted in society, by evolving meanings as well as design and use of technology. To identify relevant news articles, I conducted a keyword search on the FACTIVA database and used the LexisNexis API to automatically scrap news articles containing the label "Blockchain." In this process, I assembled a total of 241,174 news articles of varying lengths to form the corpus of text I analyzed.
I draw on category perspective, a research stream that sheds light on the role of meanings in the diffusion of technologies. While category research has provided valuable insights to understand technology diffusion, scholars in this tradition tend to leave the technology itself largely black-boxed, focusing primarily on discursive and cognitive processes surrounding the meaning of a given technology. It is, therefore, worth identifying properties associated with blockchain technology in the public discourse and investigating how the combination of these concepts and their uses for specific purposes shapes the meaning of a label - blockchain.
Moreover, category scholars have often employed discourse analysis to capture the evolving labels and associated meanings of a category. The current discourse analysis, however, is hard to scale as it requires close reading of text data, so researchers have often relied on a small set of data to investigate the broad field-level dynamics. Limitations of this method have motivated me to develop a way to apply computational techniques to analyze a massive amount of unstructured social data for theory-generating research. In this study, I employed advanced natural language process techniques to investigate the formation and evolution of the meaning of a technology category.
My analysis showed that the historical changes in the meaning structures related to a blockchain label are closely intertwined with the evolving design and use of technologies. A deeper investigation allowed me to understand that the significant shifts in meaning structures occurred when unintended use of technology attributes the negative values to the given category. In response, modifications have been made to the design and use of technology as well as narrative productions to associate new values to the category. In this way, the value dimensions were temporally associated and dissociated with the category at different points of time, evolving the meaning of the technology category. Overall, I found that it is through the constant reconfiguration of technologies and values that sustains the technology diffusion.
