Online political advertising is becoming increasingly popular as political campaigns recognize the utility of social network platforms, like Facebook, for reaching and engaging with voters. Yet, contrary to the wealth of information about campaign advertising on TV, little is known about advertising online, as comprehensive data only recently became available to scholars. Moreover, the newly available data is often aggregated, incomplete, and imprecise. Here, we present an analysis of Facebook political ad data, supplemented with funding-related meta-data obtained through human coding and a partnership with the Center for Responsive Politics. Through computational tools—namely, network analysis—we aim to use this data to describe and categorize political ad funding behavior on Facebook. Specifically, we focus on the geographic concentration of ads, and discover that most ads reach an audience in a single geographic region (i.e., U.S. state) or in a wide range of regions, and very few reach an audience spanning a small number of regions. We use this observation to partition funding entities into three groups based on their relationships to regionally-concentrated ads. We then examine the differences between these groups via bipartite networks connecting funding entities to their geographic audiences, as well as content they support. Our findings reveal that geographic impressions play an important role in online political advertising, and can be used to classify funding entities. As a result, this study represents a step toward ensuring political funding transparency and demystifying online political advertising more broadly.

随着政治运动认识到诸如Facebook之类的社交网络平台在吸引选民和与选民互动方面的作用，在线政治广告正变得越来越受欢迎。然而，与关于电视上的竞选广告的大量信息相反，对于在线广告知之甚少，因为学者们才刚刚获得全面的数据。此外，新获得的数据通常是汇总，不完整和不精确的。在这里，我们介绍了对Facebook政治广告数据的分析，并补充了通过人工编码以及与响应性政治中心的合作获得的与资金相关的元数据。通过计算工具（即网络分析），我们旨在使用这些数据来描述和分类Facebook上的政治广告资助行为。具体来说，我们专注于广告的地理位置集中，并发现大多数广告会覆盖单个地理区域（即美国州）或范围广泛的受众，而很少有广告覆盖跨少数区域的受众。我们使用此观察结果，根据资金实体与区域集中广告的关系将其划分为三类。然后，我们通过将资金实体与其地理位置的受众群体连接起来的双向网络，来研究这些群体之间的差异，以及他们所支持的内容。我们的发现表明，地理印象在在线政治广告中起着重要作用，可用于对资助实体进行分类。结果，这项研究代表了朝着确保政治资金透明度和使在线政治广告更加神秘化迈出的一步。