论文标题
腐败研究的计算方法
Computational Approaches to the Study of Corruption
论文作者
论文摘要
研究腐败带来了独特的挑战。本着计算社会科学精神的最新工作利用了新近可用的数据和方法，以对这一重要主题有了新的视角。在本章中，我们重点介绍了其中一些作品，描述了它们如何提供有关从微观到宏观量表社会腐败的结构和动态的经典社会科学问题的见解。我们认为，腐败被富有成果理解为嵌入式人和组织之间发生的集体行动问题。网络科学和基于代理的建模等计算方法可以洞悉这种情况。我们还提供了已利用用于研究腐败的各种（大）数据源。最后，我们通过强调相邻领域的工作，例如关于勾结，逃税，有组织犯罪和Darkweb的问题，以及未来工作的有前途的途径。
Studying corruption presents unique challenges. Recent work in the spirit of computational social science exploits newly available data and methods to give a fresh perspective on this important topic. In this chapter we highlight some of these works, describing how they provide insights into classic social scientific questions about the structure and dynamics of corruption in society from micro to macro scales. We argue that corruption is fruitfully understood as a collective action problem that happens between embedded people and organizations. Computational methods like network science and agent-based modeling can give insights into such situations. We also present various (big) data sources that have been exploited to study corruption. We conclude by highlighting work in adjacent fields, for instance on the problems of collusion, tax evasion, organized crime, and the darkweb, and promising avenues for future work.
