Doctoral Dissertation Research: Information, Public Opinion, and Behavior

本项目探讨专制政权中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维持对民众的控制非常重要。计划中的调查实验将衡量政治信息操纵策略（审查、造反和数字压制）的影响。随着许多社会互动进入数字空间，政府有更多的机会获取个人和社会数据。与此同时，人工智能和机器学习领域经历了前所未有的增长，微处理器的能力也同样快速增长。这些进步为政府提供了更好的工具来消化、处理并根据这些大量的个人数据做出明智的决定。该项目是了解这些常见的数据驱动信息操纵策略如何在威权政府中发挥作用和影响个人的第一步，对于高度网络化和数字化时代的现代政治和公众舆论学者来说，这是必不可少的知识。在这个项目中，使用调查实验和大n相关分析来探索专制政权中经历政治信息操纵对个人行为和意见的影响。假设政府信息操纵是隐蔽的——当政府作为信息操纵者的身份被模糊时——将向有利于政府的方向增加个人层面影响的程度。更具体地说，与更公开的政府信息操纵相比，隐蔽的信息操纵将更有说服力，将更显著地增加对国家的积极看法，将更显著地降低一个人的政治效能感，并将比公开操纵更严重地降低一个人表达意见的意愿。为了验证这些假设，将使用一个大型数据库运行一个伪实验，该数据库使用自动近重复检测识别联合文章。出现在不同新闻网站上、文本相同但评论不同的联合国有媒体文章，将在治疗组（有明星和普通用户评论的文章）和对照组（只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，将进行三项调查实验，分别测试审查制度、星图化和公开和隐蔽形式的数字压制的影响。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。该奖项反映了美国国家科学基金会的法定使命，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.