Understanding electoral violence is an urgent need in today’s world. Yet the detection and accurate measurement of electoral violence has proved elusive to political scientists. There are currently only limited macro-level (cross-national) datasets of the phenomenon, and virtually no reliable micro-level data. This paper will detail a new computational method for measuring electoral violence at the micro-level. The approach described entails the use of event-detection techniques developed as part of the University of Glasgow School of Computing Sciences’ renowned Terrier search engine platform. This method enables the generation of incident-based datasets to track electoral violence among digital-born media forms such as news webpages and social media. The resulting data can be used by political scientists and others to test theoretical propositions about the causes and consequences of electoral violence, as well as to study typical patterns of development and spread of violent activity during election periods.