HCC: Small: Net Fishing: Pulling Valuable Tweets, Feeds, and Blogs from the Online Message Stream

在过去的两年里，我们观察到在线消息流的使用呈爆炸性增长。随之而来的是信息的超载和注意力的匮乏：活跃的消息流用户现在每天在他们的个人信息流中面临数以千计的未读消息。到目前为止，尽管用户和企业对流消费问题有巨大的兴趣，但我们知道致力于这一流消费问题的学术研究很少。这项研究将为我们理解消息流的消费奠定科学基础，并为用户设计、部署和评估在这些基础上构建的新工具。本研究有两个主要目的。首先，构建计算模型，描述流读者的个人偏好，并为每个读者预测特定消息提供的价值，以及总体上特定的流贡献者提供的价值。第二个目标是设计新颖、个性化和智能的用户界面，促进更好地消化和管理在线消息流，并在流行的平台Twitter、Facebook和Google Reader上进行大规模实地研究，对这些设计进行评估。这项拟议的研究是第一批广泛检查在线消息流并从消费的角度描述消息流的研究之一。我们的模型将使我们深入了解在线消息流消费的本质，并为进一步研究提供一个理论框架。花时间创建、评论、交流和使用推文、墙上的帖子、状态更新和博客帖子。这里提出的研究承诺加深我们对消息流背后的目的、价值和社会机制的理解，并为建模贡献者、他们的贡献和消费过程创造新的计算资源。基于这些计算模型，将开发创新的可视化、推荐和界面，以重塑用户体验，并为未来消息流服务的设计提供信息。

In the past two years we have observed an explosion in the use of online message streams. With an abundance of information comes information overload and a scarcity of attention: Active message stream users now face thousands of unread messages every day in their personal streams. To date, we are aware of little academic research dedicated to this stream consumption problem, despite the enormous interest among users and businesses.This research will establish scientific foundations for our understanding of the consumption of message streams, and engineer, deploy, and evaluate new tools for users built on those foundations. This research has two principle aims. First, construct computational models that characterize the individual preferences of stream readers and predict for each reader the value provided by specific messages, and, in aggregate, specific stream contributors. The second aim is to design novel, personalized and intelligent user interfaces that facilitate better digestion and management of online message streams, and evaluate those designs in large-scale field studies on the popular platforms Twitter, Facebook and Google Reader. The proposed research is among the first to examine online message streams broadly and to characterize message streams from the perspective of consumption. Our modeling will give insights into the nature of online message stream consumption and provide a theoretical framework for further investigation.Hundreds of millions of users worldwide are ?voting with their fingers? to spend time creating, commenting on, communing over, and consuming tweets, wall posts, status updates, and blog posts. The research proposed here promises to deepen our understanding of the purpose, value, and social mechanisms underlying message streams, and to create new computational resources for modeling the contributors, their contributions, and the process of consumption. Based on these computational models, innovative visualizations, recommendations, and interfaces will be developed to reshape the user experience, and inform the design of future message stream services.