We can see an increasing number of examples where humans contribute to large-scale collective action by sharing information online. This can be in case of a disastrous event (e.g. the Haiti earthquake) or political crisis (e.g. the Kenyan election) but also less critical situations deserving the spread of information of public interest (e.g. an actual traffic jam or cancelled train). These examples have in common that even though there is some common topic or goal hovering above the information sharing activities of the individuals (e.g. coordinating help in disaster response or optimizing travel routes of people being affected by traffic disruptions) people are not necessarily talking with each other. They are just talking out loudly about the same thing (especially in critical situations when time to make decisions is rare). This suggests that there exists unintended collective action that is the substrate of the accumulated information sharing behavior of individuals. A method to capture this is the focus of this talk. I will introduce an approach that is an attempt to formalize coincidence of information sharing rather than socially-determined conditional cascading. Through the investigation of microscopic events we seek to derive insight into the macroscopic state of the World Wide Web