ABSTRACT With the advent of the information age, Open Source Intelligence (OSINT) has gained special prominence in the Intelligence Community (IC). However, the era of big data has brought numerous challenges in handling OSINT, in particular because big data comprise large volumes of unstructured data that are generated continuously. In this article, we discuss the use of OSINT in the era of big data, in particular how it relates to compiling event data, but also show that large projects with an international focus such as the Integrated Crisis Early Warning System (ICEWS) are inadequate to study political instability in the current South African context. We shift our collection efforts from mainstream media to the analysis of WhatsApp messages, since this platform has recently gained popularity and it is widely used in South Africa. We show how we build an automated data pipeline that provides near real time data on the occurrence of mass violence in South Africa. For this analysis, we make use of Natural Language Processing (NLP) toolkits in Python and build interactive dashboards to monitor the state of mass violence in South Africa.

中文翻译：

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用于当代南非冲突监控的开源情报 (OSINT)：大数据背景下的挑战和机遇

摘要 随着信息时代的到来，开源情报（OSINT）在情报界（IC）中获得了特别的重视。然而，大数据时代在处理开源情报方面带来了许多挑战，特别是因为大数据包含大量连续生成的非结构化数据。在本文中，我们讨论了 OSINT 在大数据时代的使用，特别是它与编译事件数据的关系，但也表明诸如综合危机早期预警系统 (ICEWS) 等具有国际关注度的大型项目是不够的研究当前南非背景下的政治不稳定。我们将收集工作从主流媒体转移到分析 WhatsApp 消息，因为该平台最近很受欢迎，并在南非广泛使用。我们展示了我们如何构建一个自动化数据管道，该管道提供有关南非大规模暴力事件发生的近乎实时的数据。对于此分析，我们使用 Python 中的自然语言处理 (NLP) 工具包并构建交互式仪表板来监控南非的大规模暴力状态。