Doctoral Dissertation Research: Narrative, Quantification, and the Chinese Political Diaspora

Yale University, New Haven CT

Investigators

Abstract

The investigators will use "quantitative narrative analysis" (QNA) to create a database of narratives from two diaspora-based Chinese social movements. QNA is a hybrid methodology involving aspects of in-depth qualitative research and large-N quantitative research. The methodology combines narrative theory, quantification, and computing to discover and demonstrate trends in very large collections of narrative textual information. The methodology, however, is still in its formative stages and is in need of testing and further development. In the present project, QNA will be used to create a relational database of narratives for comparing a religious social movement, called Falun Gong, and a secular, political reform social movement, the Chinese Democracy Movement. Quantitative analysis of the database will permit modeling of mobilization patterns: who did what, when, where, why and how. The database also will allow investigation of discourse patterns relevant to cultural themes and patterns of signification. By using Chinese materials, the project will both assess the generalizability of the QNA approach and adapt QNA methods and software to the particularities of Chinese. Narrative is a universal form of human communication found in the widest variety of social contexts -- from ancient texts to contemporary blogs, from religious conversion stories to courtroom testimonies. Since so much human communication is conveyed through narrative, innovative methods to exploit narrative structures to draw inferences about social life can potentially find application in diverse areas of social research. The current project will use QNA to improve our understanding of both Chinese social movements and the intersection of religion and politics. The project also will advance the frontiers of computer-assisted analysis of communication. As a Doctoral Dissertation Research Improvement award, this award will provide support to enable a promising student to establish a strong independent research career.