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.

在美国，关于广泛话题的意见日益两极分化，引起了公众话语和学术界的关注。个性化推荐系统的广泛采用已经改变了意见形成、表达、改变和传播的方式。因此，即使处于这些小生境中的个人没有明确的社会关系联系，他们的意见往往会因接触文化和意识形态群体而得到加强。该项目将使用来自亚马逊书评和购买的数据来构建一个图书共同购买和共同评论者网络，以研究意见聚类和选项极化。将特别关注四个关键问题：是否存在密集的书籍集群，集群之间的联系很少？什么类型的书会产生聚类？是否有一些书籍在这些集群之间架起了桥梁，这些书籍是否会聚集成与横切文化维度相对应的较少数量的主题？在市场更广阔的情况下，在集群之间架起桥梁的书籍销量更高;在每个集群中，在偏离核心的情况下，销量更低;还是销量相似但标准差更高？拟议的项目将利用先进的计算方法来收集和处理亚马逊网站上的图书共同购买数据和有时间戳的书评。图书将被手工编码成类别，网络分析将被用来定位这些主题在共同购买和共同评论中的结构位置。本论文对意见动力学的研究做出了三个主要贡献：1）更好地理解了在线推荐和评论系统如何反映和促进意见极化; 2）将同质性理论和模型扩展到人和文化对象的二分网络中的聚类; 3）开发新的研究方法，使用消费者购买和评论的数字痕迹来研究意见动态和两极分化。这项研究对理解和解决美国的社会分化具有实际意义。它对两极分化的原因和动态提供了一个独特但互补的视角，并可能就如何弥合分歧提出切实可行的建议。该项目也是最早使用“大数据”研究极化的项目之一，将为研究界提供新的数据集和工具。此外，研究结果可能有助于那些希望将自己的书籍瞄准更多样化的读者的作者。该项目还将促进对从事该项目的本科生和研究生的培训。