Doctoral Dissertation Research: Examining Social Clustering and Division via Patterns of Purchasing and Reviewing

博士论文研究：通过购买和审查模式审视社会集群和分裂

• 批准号: 1409593
• 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: 2014-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1409593&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Examining; Social

The growing polarization of opinions in America on a wide range of topics has attracted attention in both public discourse and academia. Widespread adoption of personalized recommender systems has transformed the way that opinions are formed, expressed, changed and disseminated. As a consequence, opinions tend to be reinforced by exposure to cultural and ideological grouping even when individuals within those niches are not explicitly tied by social relations. This project will use data from Amazon book reviews and purchases to construct a book co-purchase and co-reviewer network with which to study opinion clustering and polarization of options. Particular attention will be directed to four key questions: Are there dense clusters of books, with few ties between the clusters? What genres of books produce clustering? Are there sorts of books that bridge between the clusters, and do these books then cluster into a smaller number of topics that correspond to crosscutting cultural dimensions? Do books that bridge between clusters enjoy greater sales, given the broader market, fewer sales, given their deviation from the core in each cluster, or similar sales but with a higher standard deviation? The proposed project will make use of advanced computational methods to collect and process book co-purchasing data and time-stamped book reviews from Amazon.com. Books will be hand-coded into categories and network analysis will be used to locate the structural positions of those topics in the co-purchase and co-review. This dissertation makes three principal contributions to research on opinion dynamics: 1) a better understanding of how online recommender and review systems both reflect and promote opinion polarization, 2) the extension of theories and models of homophily to clustering within bipartite networks of people and cultural objects; 3) the development of novel research methods that use digital traces of consumer purchases and reviews to study opinion dynamics and polarization. This research has practical implications for understanding and addressing social divisions in America. It provides a unique but complementary perspective on the causes and dynamics of polarization and may yield practical suggestions for ways to bridge divisions. This project is also one of the first to use "big data" to study polarization, and will provide the research community with new datasets and tools. In addition, the results may be helpful for authors who want to target their books to a more diverse audience. The project will also advance the training of undergraduate and graduate students who work on the project.

在广泛的主题上，美国观点的两极分化越来越多，引起了公众话语和学术界的关注。广泛采用个性化推荐系统已经改变了观点形成，表达，更改和传播的方式。结果，即使在这些生态位中的个人并没有明确地与社会关系束缚时，也会通过暴露于文化和意识形态群体来加强观点。该项目将使用亚马逊图书评论和购买中的数据来构建书籍共购买和共同评论者网络，并使用该网络来研究期权的意见聚类和两极分化。特别关注的是四个关键问题：是否有密集的书类，群集之间几乎没有关系？哪些类型的书籍会产生聚类？是否有各种书籍之间桥接的书籍，然后这些书将与跨越文化维度相对应的较少的主题聚集在一起？鉴于更广泛的市场，更少的销售，鉴于每个集群中的核心或类似的销售额，但标准偏差更高的销售额，销量更少，销售量更少，销售量更少，销售量较少？拟议的项目将利用高级计算方法收集和处理书籍共同购买数据以及来自Amazon.com的时间戳记的书评。书籍将被手工编码为类别，网络分析将用于在共购买和共同评论中找到这些主题的结构位置。本论文对意见动态研究做出了三项主要贡献：1）更好地理解在线推荐和审查系统如何反映和促进意见两极分化，2）将理论和同质的理论和模型扩展到聚集在人和文化对象的双方网络中； 3）使用数字痕迹的消费者购买和评论来研究意见动态和两极分化的新型研究方法的发展。这项研究对理解和解决美国的社会分裂具有实际意义。它为极化的原因和动态提供了独特但互补的观点，并可能对桥接分裂的方式产生实用的建议。该项目也是最早使用“大数据”研究两极分化的项目之一，并将为研究社区提供新的数据集和工具。此外，结果可能对想要将书籍定位为更多样化受众的作者有帮助。该项目还将推进从事该项目的本科生和研究生的培训。