公益研究

如何在非营利组织和慈善事业研究中，引入计算社会科学(Computational Social Science, CSS)方法?本文从研究设计视角作出解答，通过梳理一系列相关的计算社会科学方法，强调了其在非营利组织和慈善事业研究领域中的关键应用。我们将“计算社会科学”定义为一系列涵盖数据管理、概念表征、数据分析和可视化等环节的计算密集型实证方法，其蕴含“社会性”,可服务于各类定量、定性以及混合方法研究中，为理论化奠定坚实基础。我们使用计算社会科学构建了非营利研究领域内规模最大、最全面的学术参考数据库——非营利组织和慈善事业研究知识基础设施(Knowledge Infrastructure of Nonprofit and Philanthropic Studies, KINPS),从而展示了将CSS引入该领域的前景。此外，我们通过应用CSS来构建和分析KINPS,能够更好地理解与推动本领域的学术发展。最后，我们指出了应用CSS时需注意的问题，并为未来运用CSS方法和KINPS数据库的研究提出了建议。

How can computational social science( CSS) methods be applied in nonprofit and philanthropic studies? This paper summarizes and explains a range of relevant CSS methods from a research design perspective and highlights key applications in our field. We define CSS as a set of computationally intensive empirical methods for data management, concept representation, data analysis, and visualization. What makes the computational methods “social” is that the purpose of using these methods is to serve quantitative, qualitative, and mixed-methods social science research, such that theorization can have a solid ground. We illustrate the promise of CSS in our field by using it to construct the largest and most comprehensive database of scholarly references in our field, the Knowledge Infrastructure of Nonprofit and Philanthropic Studies( KINPS).Furthermore, we show that through the application of CSS in constructing and analyzing KINPS,we can better understand and facilitate the intellectual growth of our field. We conclude the article with cautions for using CSS and suggestions for future studies implementing CSS and KINPS.