Retrospective Relatedness Reconstruction
提出一种基于搜索引擎的回顾性关联重构方法（3R），用于收集随时间变化的自适应社交网络的历史数据，并展示了其在分析2005-2009年美国金融危机中92位关键人物社交网络演变和情绪变化中的应用。
Examination of temporally changing adaptive social networks has been difficult given the need for extensive and usually real-time data collection. Building from interdisciplinary advances, the authors propose a web search engine–based method (called retrospective relatedness reconstruction or 3R) for collecting approximated historical data of temporally changing adaptive social networks. As quantifying relatedness among people in social networks leads to difficulty in assigning proper weights to relationship ties, 3R offers a means for assessing relatedness between people over time. Additionally, 3R can be applied beyond people relatedness to include word associations. To illustrate these two novel contributions, the authors reconstructed the temporal evolution of a social network from 2005 to 2009 of 92 individuals (key leaders) related to the U.S. financial crisis and also examined the temporal evolution of social sentiment (i.e., fear, shame, blame, confidence) related to the same 92 individuals. We found several illustrative cases where temporal changes in centrality and/or sentiment captured actual events related to these individuals during this time period.