Chinese Computational Sociology

Abstract

Abstract While applications of machine learning (ML) and natural language processing (NLP) methods have grown in the social sciences within diverse international contexts, these methods remain inherently Eurocentric and strikingly challenging to apply to non-European languages. There is an urgent need for decolonial reconstructions of ML and NLP applications within the social sciences, particularly in meaningfully reconfigured applications of ML and NLP to non-Western contexts. Endeavoring to answer such a cogent calling, this chapter reviews the existing literature that applies machine learning and NLP methods to sociological analyses of Chinese-language contexts. Synthesizing existing research, the authors introduce and establish a new and cutting-edge subfield situated at the intersections of China studies, computer science, and sociology: ‘Chinese computational sociology.’ Contributing the first review of the state of Chinese computational sociology, this chapter outlines the various challenges facing applications of ML and NLP methods for studying social issues in Chinese-language contexts, and suggests possible solutions to such limitations. Beyond existing challenges and solutions, this chapter critically considers future trajectories for Chinese computational sociology as a subfield in its own right.