Vlogcast yourself: nonverbal behavior and attention in social media

Abstract

We introduce vlogs as a type of rich human interaction which is multimodal in nature and suitable for new large-scale behavioral data analysis. The automatic analysis of vlogs is useful not only to study social media, but also remote communication scenarios, and requires the integration of methods for multimodal processing and for social media understanding. Based on works from social psychology and computing, we first propose robust audio, visual, and multimodal cues to measure the nonverbal behavior of vloggers in their videos. Then, we investigate the relation between behavior and the attention videos receive in YouTube. Our study shows significant correlations between some nonverbal behavioral cues and the average number of views per video.