Temporal patterns in social media streams: Theme discovery and evolution using joint analysis of content and context

Online social networking sites such as Flickr and Facebook provide a diverse range of functionalities that foster online communities to create and share media content. In particular, Flickr groups are increasingly used to aggregate and share photos about a wide array of topics or themes. Unlike photo repositories where images are typically organized with respect to static topics, the photo sharing process as in Flickr often results in complex time-evolving social and visual patterns. Characterizing such time-evolving patterns can enrich media exploring experience in a social media repository. In this paper, we propose a novel framework that characterizes distinct timeevolving patterns of group photo streams. We use a nonnegative joint matrix factorization approach to incorporate image content features and contextual information, including associated tags, photo owners and post times. In our framework, we consider a group as a mixture of themes

• Type: Journal
• Year: 2009
• Where: ICMCS
• Authors: Yu-Ru Lin, Hari Sundaram, Munmun De Choudhury, Aisling Kelliher
• Keywords: ICMCS 2009, Image, Image Content, Multimedia, Photo