CHS: Small: Auditing Critical Dependencies Between Online Media Platforms

这项研究将审计主要在线媒体平台之间的依赖关系，重点是主要搜索引擎，并调查它们对社交媒体平台内容的依赖程度。近年来，网络集中在少数几个吸引了大部分人关注和大部分内容的巨型平台。社交媒体和搜索引擎尤其主宰了人们的在线时间，对许多用户来说，它们实际上是“主页”。随着这些媒体平台变得越来越突出，人们也对它们创造和塑造网络空间的能力感到担忧。所有大型在线平台都使用社会技术算法对内容进行排名、过滤、推荐和调整，从而以牺牲其他信息为代价为某些信息提供特权。尽管大众媒体一直以这种方式运作，但令人新奇的担忧是，实现这些过程的算法是不透明的，使得它们难以理解、非中间或竞争。算法审计已成为围绕“黑箱”系统提高透明度和问责制的有力手段，但现有的绝大多数审计未能解决主要在线媒体平台之间的依赖关系。该项目旨在回答几个高级问题，包括：搜索结果中有多少链接到社交媒体？搜索结果中出现了哪些社交媒体平台和作者？指向社交媒体的链接如何因查询而异？社交媒体的结果是个性化的吗？到社交媒体的链接是增加了内容的多样性，还是成为了传播错误信息的工具？至于对搜索引擎与YouTube和Twitter的同时审计，将调查更具体的问题，即社交媒体网站上的算法(如“赞”推荐和热门话题或视频)如何影响搜索结果。此外，由于谷歌搜索和必应都集成了Twitter和YouTube的专门搜索组件，因此同步审计将联合调查这两个平台上的算法是如何交互的。为了进行这些算法审计，混合技术将从真实用户的角度出发，将仔细控制的实验与审计师创建的模拟在线身份相结合。这允许回答有关算法管理的影响的问题，以及揭示其一些潜在原因。审计在线平台时的一大挑战是实现生态有效性。在这里，这意味着选择能够代表真人执行的查询。为了应对这一挑战，这项研究将利用一个由350多名参与者组成的小组提供的独特的谷歌搜索查询数据集。这组查询将通过从其他来源精选的其他术语进行扩展，并将使用自动补全建议使查询多样化。这一新算法审计方法的结果将对普通公众有用，加强他们的媒体素养，以及平台设计者本身。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This research will audit the dependencies between major online media platforms, with a focus on major search engines, and investigate the extent to which they rely on content from social media platforms. In recent years, the web has centralized around a small number of mega-platforms that attract the bulk of people's attention and the majority of content. Social media and search engines in particular dominate people's online time, and serve as de-facto "homepages" for many users. As these media platforms have grown to prominence, so too have concerns about their power to create and shape online spaces. All of the large online platforms use socio-technical algorithms to rank, filter, recommend, and moderate content, thus privileging some information at the expense of other information. Although mass media has always functioned this way, the novel concern is that the algorithms that implement these processes are opaque, making them difficult to understand, disintermediate, or contest. Algorithm auditing has emerged as a powerful approach to increase transparency and accountability around "black-box" systems, but the vast majority of existing audits fail to grapple with the dependencies between major online media platforms. This project aims to answer several high-level questions, including: What fraction of search results link to social media? What social media platforms and authors appear in search results? How do links to social media vary by query? Are results for social media personalized? Do links to social media increase content diversity, or are they a vehicle for misinformation? With respect to simultaneous audits of search engines versus YouTube and Twitter, more specific questions will be investigated about how the algorithms on the social media sites (such as "like" recommendations and trending topics or videos) influence search results. Further, because Google Search and Bing both integrate specialized search components from Twitter and YouTube, simultaneous audits will jointly investigate how the algorithms on these pairs of platforms interact. To conduct these algorithm audits, hybrid techniques will combine carefully controlled experiments from the vantage point of real users with simulated online identities created by the auditor. This allows answering questions about the impact of algorithmic curation, as well as revealing some of its underlying causes. One major challenge when auditing online platforms is achieving ecological validity. Here, this means selecting queries that are representative of those executed by real people. To address this challenge, the research will leverage a unique dataset of Google Search queries from a panel of over 350 participants. This set of queries will be expanded with additional terms curated from other sources, and queries will be diversified using autocomplete suggestions. The results of this new algorithm audit methodology will be useful to the general public, strengthening their media literacy, as well as to the designers of the platforms themselves.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.