In this article, we study how media-rich social networks provide additional insight into familiar multimedia research problems, including tagging and video ranking. These social groups are an important source of information to organize and to manage multimedia data. Furthermore, popular websites with sophisticated media sharing and notification features allow users to stay in touch with friends and loved ones these sites also help to form explicit and implicit social groups. The scale of the data necessitates new research for making sense of such content. First, the presence of near-ubiquitous low-cost computing and communication technologies has enabled people to access and share information at an unprecedented scale. This research area is important for several reasons. This paper reviews the state of the art and some emerging issues in research areas related to pattern analysis and monitoring of web-based social communities. Predicting meme volume and ~17% for their lifespan. Words outperform a concurrence model, and the average error is ~2% for The joint statistical model of visual memes and We perform two quantitative evaluations for annotating visual memes and
Videos contain remixed content, and it is apparent that traditional news mediaĪnd citizen journalists have different roles in disseminating remixed content. In these two events, a high percentage of More than 40,000 videos on two prominent news events in 2009: the election in Experiments are carried out on with over 2 million video shots from We model content interactions on YouTube with visual memes,ĭefining several measures of influence and building predictive models for meme We further augment visual memes with text, via a statistical model of Visual memesĪre extracted by scalable detection algorithms that we develop, with highĪccuracy. Segments, for tracking such latent video interactions at scale. We propose visual memes, or frequently re-posted short video
To video feed), and latent interactions (such as quoting, or remixing parts ofĪ video). Social information networks, such as YouTube, contains traces of bothĮxplicit online interaction (such as "like", leaving a comment, or subscribing The video server is a standalone custom C++ application that serves remixed Flash Video files over HTTP. Both the web service and the gallery site are PHP5 applications running on the Apache web server, using a MySQL database for persistence. The web service adheres to the REST architectural style for distributed hypermedia systems to ensure scalability and allow the use of standard web intermediaries such as proxy caches. It communicates with the web service using XML messages sent via HTTP. The client is a Macromedia Flash application and thus will run within any web browser that supports the Flash Player 8 plug-in. The International Remix system consists of four components (see Figure 1): a client that runs within the end user’s web browser, a web service for persistent storage and query of remix metadata, a video server that handles on-demand splicing and serving of remixed video from multiple sources, and a gallery site for browsing and viewing submitted remixes. Components of the International Remix system.
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