Improving audience engagement and facilitating business planning with temporal data analytics

通过时态数据分析提高受众参与度并促进业务规划

• 批准号: 488740-2015
• 负责人: Collins, Christopher
• 金额: $ 1.82万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=586381
• 关键词: Improving; audience; engagement; facilitating; business

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.

DeviantArt(DA)是一个旨在展示用户创作的视觉艺术项目的社交网络，它试图将上传到社区的各种艺术作品的数据，以及围绕这些艺术贡献进行对话的人的数据转化为商业行动。DA社区拥有超过2500万名成员和2.5亿份个人作品，主要迎合视觉艺术家的需求，他们根据现有媒体的主题和想法创作原创和衍生作品，包括受欢迎的电视节目和漫画书。 在这项研究项目中，克里斯托弗·柯林斯博士和他的研究团队将创建新的视觉分析工具，利用DA和网络上其他开放数据源的流数据。这些工具将使DA的编辑团队能够实时探索和了解其用户社区的趋势如何反映(或许是预测)媒体在其他平台上的受欢迎程度。该项目的目标是为DA创建基于网络的商业分析解决方案，以便能够清楚地确定哪些主题和媒体特许经营在其社区中流行和新兴，以便将广告销售瞄准适当的市场。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，为特定的媒体特许经营权量身定做。