Abstract—Social information networks, such as YouTube, con-tains traces of both explicit online interaction (such as “like”, leaving a comment, or subscribing to video feed), and latent interactions (such as quoting, or remixing parts of a video). We propose visual memes, or frequently re-posted short video segments, for detecting and monitoring such latent video in-teractions at scale. Visual memes are extracted by scalable detection algorithms that we develop, with high accuracy. We further augment visual memes with text, via a statistical model of latent topics. We model content interactions on YouTube with visual memes, defining several measures of influence and building predictive models for meme popularity. Experiments are carried out on with over 2 million video shots from more than 40,000 videos on two prominent news events in 2009: the election in Iran and the swine flu epidemic. In these two events, a high percentage of videos contain remixed content, and it is apparent that traditional news media and citizen journalists have different roles in disseminating remixed content. We perform two quantitative evaluations for annotating visual memes and predicting their popularity. The joint statistical model of visual memes and words outperform a concurrence model, and the average error is is ±2 % for predicting meme volume and ±17% for their lifespan. I.

Duplicate image detection in a stream of web visual data

Creating compelling multimedia productions is a nontrivial task. This is as true for creating professional content as it is for nonprofessional editors. During the past 20 years, authoring networked content has been a part of the research agenda of the multimedia community. Unfortunately, authoring has been seen as an initial enterprise that occurs before ‘real ’ content processing takes place. This limits the options open to authors and to viewers of rich multimedia content for creating and receiving focused, highly personal media presentations. This article reflects on the history of multimedia authoring. We focus on the particular task of supporting socially-aware multimedia, in which the relationships within particular social groups among authors and viewers can be exploited to create highly personal media experiences. We provide an overview of the requirements and characteristics of socially-aware multimedia authoring within the context of exploiting community content. We continue with a short historical perspective on authoring support for these types of situations. We then present an overview of a current system for supporting socially-aware multimedia authoring within the community content. We conclude with a discussion of the issues that we feel can provide a fruitful basis for future multimedia authoring support. We argue that providing support for socially-aware multimedia authoring can have a profound impact on the nature and architecture of the entire multimedia