Digital content, like news presented on screens at public places (e.g., subway stations) is pervasive. Usually it is not possible for passers-by to conveniently interact with such public displays, as content is not interactive or responsive. Especially news screens are normally showing one news article after another, reducing the amount of information fitting the screen dimensions. In this paper we developed a collaborative newspaper application based on an adaptive scrolling algorithm, that manages scrolling of the same content for several users simultaneously. We are using head-mounted eye trackers to track people’s gaze on the screen and detect their reading positions. Thus we offer the possibility to display news texts which are larger than the screen height, as the system automatically adapts the text scrolling to the person’s reading behavior. In a user study with fifteen participants we investigated how the scrolling algorithm affects the reading speed of people in single- and multi-user scenarios. Further we evaluated the work load while using the system. The results show that the adaptive scrolling algorithm does not negatively influence the reading speed, neither in single- nor in a multi-user reading scenario.