Online public discussion spaces such as Usenet news groups are rich social environments. The social dynamics within the community are not obvious by looking at the strings of text-based content. Only a careful reading of the threads allows the viewer to discern complexities and nuances of social interactions. Expressive visualization, however, is an alternative medium for effectively conveying such information. In order to animate the dynamic social qualities found within the static data of a Usenet interface, motion is used as the communicative agent for this visual translation. The goal of the research is to isolate those elements that comprise visual motion, such as position, direction, speed, and time, in order to develop a visual language through which the social complexities of online communities can be communicated. A series of studies exploring this problem are being carried out using a theoretical framework inspired by cognitive and artistic precedents. We hope these investigations result in an understanding of how motion can be successfully employed as a visual language for social expression.