Data and methods development are key to improve our ability to forecast conflict. Relatively new data sources such as mobile phone and social media data or images have received widespread attention in conflict research recently. Such data do oftentimes not cover substantial parts of the globe or they are difficult to obtain and manipulate which makes regular updating challenging. These sometimes vast amounts of data can also be computationally and financially costly. The data source we propose instead is cheap, readily and openly available, updated in real-time, and it provides global coverage: Wikipedia. We argue that the number of country page views can be regarded as a measure of increased interest or salience whereas the number of page changes can be regarded as a measure of controversy between competing political views. We expect these predictors to be particularly successful in capturing tensions before a conflict escalates or after a period of peace is followed by violence again, for instance electoral violence. Predicting fatalities after calm periods is particularly challenging as past violence is not a suitable predictor. We test our argument by predicting changes in battle-related deaths in Africa on the country-month level. We find evidence that country page views do increase predictive performance while page changes do not. Contrary to our expectation, our model seems to capture long-term trends better than sharp short-term changes.