Protest event analysis is a key method to study social movements, allowing to systematically analyze protest events over time and space. However, the manual coding of protest events is time-consuming and resource intensive. Recently, advances in automated approaches offer opportunities to code multiple sources and create large data sets that span many countries and years. However, too often the procedures used are not discussed in details and, therefore, researchers have a limited capacity to assess the validity and reliability of the data. In addition, many researchers highlighted biases associated with the study of protest events that are reported in the news. In this study, we ask how social scientists can build on electronic news databases and computational tools to create reliable PEA data that cover a large number of countries over a long period of time. We provide a detailed description our semiautomated approach and we offer an extensive discussion of potential biases associated with the study of protest events identified in international news sources.

抗议事件分析是研究社会运动的关键方法，可以系统地分析不同时间和空间的抗议事件。然而，抗议事件的手动编码是耗时且资源密集的。最近，自动化方法的进步为编码多个来源和创建跨越许多国家和年份的大型数据集提供了机会。然而，所使用的程序往往没有详细讨论，因此，研究人员评估数据有效性和可靠性的能力有限。此外，许多研究人员强调了与新闻报道的抗议事件研究相关的偏见。在这项研究中，我们询问社会科学家如何在电子新闻数据库和计算工具的基础上创建可靠的 PEA 数据，这些数据在很长一段时间内覆盖了大量国家。我们详细描述了我们的半自动方法，并广泛讨论了与国际新闻来源中确定的抗议事件研究相关的潜在偏见。