Doctoral Dissertation Research: Information, Public Opinion, and Behavior

这个项目探讨了在专制政权的政治信息操纵如何影响个人的行为，态度和意见。这个项目对于我们理解专制政权如何利用社交媒体和大数据获得民众支持和保持对人口的控制非常重要。计划中的调查实验将衡量政治信息操纵策略（审查，astroturfing和数字镇压）的影响。 随着大部分社会互动进入数字空间，政府可以更容易地访问个人和社会数据。与此同时，人工智能和机器学习领域也经历了前所未有的增长，沿着微处理器能力的快速增长。这些进步为政府提供了更好的工具来消化、处理这些海量个人数据，并根据这些数据做出明智的决策。这个项目是了解这些常见的数据驱动的信息操纵策略如何在威权政府中运作和影响个人的第一步，这是高度网络化和数字化时代现代政治和舆论学者的基本知识。本研究采用问卷调查和大样本调查相结合的方法，探讨了政治信息操纵对个体行为和观点的影响，N相关分析。假设政府信息操纵是隐蔽的，即当政府作为信息操纵者的身份被掩盖时，将朝着有利于政府的方向增加个人水平效应的大小。更具体地说，与公开的政府信息操纵相比，隐蔽的信息操纵将更有说服力，将更显着地增加对国家的积极看法，将更显着地降低一个人的政治效能感，并将减少一个人表达意见的意愿。为了检验这些假设，将使用自动近似重复检测识别的联合文章的大型数据库运行伪实验。出现在不同新闻网站上的具有相同文本但不同评论的联合官方媒体文章将在治疗组（具有astroturfers和普通用户评论的文章）和对照组（仅具有普通用户评论的文章）之间进行比较。针对上述每个假设的变量将使用统计和自然语言处理方法从文本中提取。此外，还将进行三项调查实验，分别测试公开和隐蔽形式的审查，astroturfing和数字镇压的影响。这项工作对于理解现代专制政权如何利用社交媒体引导公众舆论、动员政权支持和遣散反对者至关重要。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project explores how political information manipulation in authoritarian regimes can affect the behaviors, attitudes, and opinion of individuals. This project is important to our understanding of how authoritarian regimes gain popular support and maintain control over populations using social media and big data. Planned survey experiments will measure the effect of political information manipulation tactics (censorship, astroturfing, and digital repression). As much of social interaction has moved into a digital space, governments have greater access to personal and social data. At the same time, the fields of artificial intelligence and machine learning have experienced unprecedented growth along with a similarly rapid growth in the power of microprocessors. These advances have given governments better tools to digest, process, and make informed decisions based on these massive stores of personal data. This project is a first step toward understanding how these common data-driven information manipulation tactics work and impact individuals in authoritarian governments, essential knowledge for scholars of modern politics and public opinion in a highly networked and digital age.In this project, the effects of experiencing political information manipulation on individual behaviors and opinion in authoritarian regimes are explored using both survey experiments and large-N correlational analyses. It is hypothesized that government information manipulation that is covert---when the identity of the government as information manipulator obscured---will increase the magnitude of individual-level effects in a direction favorable to the government. More specifically, when compared to more overt government information manipulation, covert information manipulation will be more persuasive, will more dramatically increase positive perceptions of the state, will more dramatically decrease one's sense of political efficacy, and will decrease one's willingness to express opinions more than overt manipulation. To test these hypotheses, a pseudo experiment will be run using a large database of syndicated articles identified using automated near-duplicate detection. Syndicated state media articles, appearing on different news websites with identical text but different comments, will be compared across a treatment group (articles with comments from astroturfers and ordinary users) and a control group (articles with comments from only ordinary users). Variables targeting each of the hypotheses above will be drawn from the text using statistical and natural language processing methods. Additionally, three survey experiments will be conducted to test, respectively, the effect of censorship, astroturfing, and digital repression in overt and covert forms. This work is critical to understand how modern authoritarian regimes leverage social media to guide public opinion, mobilize regime support, and demobilize opponents.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.