Improving audience engagement and facilitating business planning with temporal data analytics

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DeviantArt (DA), a social network designed to showcase user-created visual art projects, seeks to translate data about various artworks uploaded to the community, as well as the people engaged in conversations surrounding these artistic contributions, into business actions. Comprising more than 25 million members and 250 million individual submissions, the DA community primarily caters to visual artists who produce original and derivative works based on motifs and ideas borrowed from existing media franchises, including popular TV shows and comic books. In this research project, Dr. Christopher Collins and his research team will create new visual analytics tools which draw on streaming data from DA and other open data sources on the web. These tools will allow editorial teams at DA to explore and understand how the trends in their user community are reflective (and perhaps predictive) of the popularity of media on other platforms, in real time. The goal of this project is to create web-based business analytics solutions for DA to be able to clearly determine which topics and media franchises are popular and emerging in their community, in order to target advertising sales to appropriate markets. Through better understanding the relationship between the DA user community behavior and the plot shifts and release dates of media such as television shows, DA will be able to create an data-driven system for advertising pricing, tailored to specific media franchises.