Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
534365 | Pattern Recognition Letters | 2016 | 8 Pages |
•Clustering diverse images shared on social forums produces meaningful groups.•User behavior patterns on social media can be characterized with image distributions.•Users exhibit diverse preference patterns for images they engage with.•Users often exhibit distinct patterns between supply and consumption behavior.•Salient users can be identified by non-parametric statistical anomaly analysis.
This work addresses the novel problem of analyzing individual user’s behavioral patterns regarding images shared on social forums. In particular, we present an image-oriented economic perspective: the first activity mode of sharing or posting on social forums is interpreted as supply; and another mode of activity such as commenting on images is interpreted as consumption. First, we show that, despite the significant diversity, images in social forums can be clustered into semantically meaningful groups using modern computer vision techniques. Then, users’ supply and consumption profiles are characterized based on the distribution of images which they engage with. We then present various statistical analyses on real-world data, which show that there is significant difference between the images users supply and consume. This finding suggests that the flow of images on social network should be modeled as a bi-directional graph. In addition, we introduce a statistical approach to identify users with salient profiles. This approach can be useful for social multimedia services to block users with undesirable behavior or to identify viral content and promote it.