Combining text analytics and network path extraction to trace CSR in the social sciences: Intellectual structures and diffusion trajectories

Abstract

AbstractCorporate social responsibility (CSR) has evolved over time into a mature interdisciplinary scientific field. However, there is a lack of research to explore the disciplinary association patterns and diffusion trajectories of scientific knowledge within this field. This research proposes a knowledge tracing framework that combines text analysis based on scientific texts and main path extraction based on citation networks to fill this gap. This framework is implemented in a dataset containing 15,949 papers related to CSR in the social sciences published from 1969 to 2022. This study identifies 19 main research directions within this field and their five growth trends. Combined with disciplinary categories of publication venues, both the disciplinary origins and disciplinary association patterns of these knowledge contents are also revealed. Besides that, three knowledge diffusion paths are obtained, which meticulously reveal the knowledge evolution and paradigm shift. Aside from the methodological novelty and result scarcity, this study also identifies research streams and potential opportunities. To begin with, CSR‐related studies have shown the tendency of microscopic and interdisciplinary. Then, related research methods show the tendency to be complicated and focus on causal logic. On this basis, some future agendas of CSR are also proposed in this work.