论文标题
从GDELT数据库采矿国际政治规范
Mining International Political Norms from the GDELT Database
论文作者
论文摘要
长期以来，研究人员一直对规范在多代理系统中的代理行动中所起的作用感兴趣。在将人类社会的规范概念形式化，并将其适应开放软件系统的政府以及对人类和人工社会中的规范过程的模拟方面，已经完成了许多工作。但是，在应用规范MAS机制上以了解人类社会规范的工作相对较少。 这项工作在国际政治的背景下调查了这个问题。使用GDELT数据集，其中包含从新闻报道中提取的国际事件的机器编码记录，我们提取了国际事件的双边序列，并应用了贝叶斯规范挖掘机制，以识别最能解释观察到的行为的规范。统计评估表明，规范模型比概率离散事件模型要拟合数据明显更好。
Researchers have long been interested in the role that norms can play in governing agent actions in multi-agent systems. Much work has been done on formalising normative concepts from human society and adapting them for the government of open software systems, and on the simulation of normative processes in human and artificial societies. However, there has been comparatively little work on applying normative MAS mechanisms to understanding the norms in human society. This work investigates this issue in the context of international politics. Using the GDELT dataset, containing machine-encoded records of international events extracted from news reports, we extracted bilateral sequences of inter-country events and applied a Bayesian norm mining mechanism to identify norms that best explained the observed behaviour. A statistical evaluation showed that the normative model fitted the data significantly better than a probabilistic discrete event model.
