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

HCC：小型：网络钓鱼：从在线消息流中提取有价值的推文、提要和博客

• 批准号: 1017697
• 负责人: Joseph Konstan
• 金额: $ 50万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1017697&HistoricalAwards=false
• 关键词: HCC; Small; Net; Fishing; Pulling

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.

在过去的两年里，我们观察到在线信息流的使用出现了爆炸式增长。随着信息的丰富，信息过载和注意力的缺乏：活跃的消息流用户现在每天在他们的个人流中面临数千条未读消息。到目前为止，我们知道很少有学术研究致力于这个流消费问题，尽管在用户和企业的巨大兴趣。这项研究将建立科学的基础，为我们的理解消息流的消费，工程师，部署和评估新的工具，为用户建立在这些基础上。这项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，以及聚合的特定流贡献者。第二个目标是设计新颖、个性化和智能的用户界面，以便于更好地消化和管理在线消息流，并在流行平台Twitter、Facebook和Google Reader上进行大规模实地研究，评估这些设计。拟议的研究是第一次广泛地研究在线消息流，并从消费的角度来表征消息流。我们的建模将深入了解在线消息流消费的本质，并为进一步的调查提供理论框架。用手指投票花时间创建，评论，交流和消费tweets，wall posts，状态更新和博客帖子。 这里提出的研究有望加深我们对消息流的目的，价值和社会机制的理解，并创建新的计算资源来建模贡献者，他们的贡献和消费过程。 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。