We present a data-driven approach to discover different styles that people use to present themselves in online video blogging (vlogging). By vlogging style, we denote the combination of conscious and unconscious choices that the vlogger made during the production of the vlog, affecting the video quality, appearance, and structure. A compact set of vlogging styles is discovered using clustering methods based on a fast and robust spatio-temporal descriptor to characterize the visual activity in a vlog. On 2268 YouTube vlogs, our results show that the vlogging styles are differentiated with respect to the vloggers' level of editing and conversational activity in the video. Furthermore, we show that these automatically discovered styles relate to vloggers with different personality trait impressions and to vlogs that receive different levels of social attention.