Doctoral Dissertation Research: The Strength of Long Ties

博士论文研究：长期关系的力量

• 批准号: 1434164
• 负责人: Michael Macy
• 金额: $ 1.19万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1434164&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Strength; Long

40 years since the pioneering work of sociologist, Mark Granovetter, on the "strength of weak ties," numerous studies have confirmed his counter-intuitive thesis that individuals are more likely to acquire novel information from an acquaintance who bridges long network distances than from a close friend. Although the importance of bridge ties for diffusion has been well documented, the focus has primarily been on comparing the relational strength of ties embedded in tightly knit circles vs. the relational strength of ties that bridge long network distances, rather than examining tie strengths of bridge ties that span varying network distances. Drawing on population-scale data from Twitter and other social/communication networks, this project will (a) test the proposition that bridging ties tend to be weaker with the network distance they span, (b) develop an explanation for the relationship between the strength and span-length of bridging ties using statistical and simulation approaches, and (c) further explore the variation in these relationships across countries of different cultures and economic development. This study will contribute to research across the social sciences, including studies of diffusion and contagion, network evolution, social capital, and labor market processes. The development and dissemination of effective methods to collect, analyze, and compare multiple networks constituted by hundreds of millions of individuals will contribute to the social science community that primarily relied on survey-based egocentric network data. The project will also contribute to graduate training on the use of distributed and parallel cloud-computing tools for studying population-scale social networks

自从社会学家马克·格拉纳诺维特（Mark Granovetter）开创性的工作关于“弱关系的力量”以来，许多研究已经证实了他的违反直觉论点，即个人更有可能从熟人那里获得长期网络距离的新信息，而不是从密友那里获得长期的网络距离。尽管桥梁关系对于扩散的重要性已经有充分的文献记录，但重点主要是在比较紧密编织圆圈中嵌入的纽带的关系强度，而不是桥接长网络距离的关系强度，而不是检查桥梁领带的扎带扎带强度，从而跨越了网络距离。该项目借鉴了Twitter和其他社会/通信网络的人口量表数据，将测试桥接关系在跨越网络距离中往往较弱的主张，（（b）为使用统计和模拟方法的桥接纽带之间的强度和桥梁长度之间的关系提供了解释，以及（c）进一步探索不同文化和经济发展的关系的变化。这项研究将有助于整个社会科学的研究，包括扩散和传染，网络进化，社会资本和劳动力市场过程的研究。有效的方法的开发和传播是收集，分析和比较数亿个人构成的多个网络的方法，将为社会科学界做出贡献，该社会社区主要依靠基于调查的Egipentric网络数据。该项目还将有助于研究分布式和平行云计算工具的研究生培训，以研究人群规模的社交网络