Improving audience engagement and facilitating business planning with temporal data analytics

DeviantArt（DA）是一个旨在展示用户创建的视觉艺术项目的社交网络，旨在将上传到社区的各种艺术作品的数据以及参与围绕这些艺术贡献的对话的人转化为商业行为。DA社区拥有超过2500万会员和2.5亿份个人作品，主要面向视觉艺术家，他们根据现有媒体特许经营权的主题和想法制作原创和衍生作品，包括流行的电视节目和漫画书。 在这个研究项目中，Christopher柯林斯博士和他的研究团队将创建新的可视化分析工具，这些工具将利用来自DA和网络上其他开放数据源的流数据。这些工具将使DA的编辑团队能够探索和理解他们的用户社区的趋势如何反映（也许是预测）媒体在其他平台上的流行程度，在真实的时间。该项目的目标是为DA创建基于网络的业务分析解决方案，以便能够清楚地确定哪些主题和媒体特许经营权在其社区中流行和新兴，以便将广告销售定位到适当的市场。通过更好地了解DA用户社区行为与电视节目等媒体的情节变化和发布日期之间的关系，DA将能够创建一个数据驱动的系统， 广告定价，为特定的媒体专营权量身定制。

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.