Diffusion of User Tracking Data in the Online Advertising Ecosystem
Diffusion of User Tracking Data in the Online Advertising Ecosystem
复制标题
在线广告生态系统中用户跟踪数据的扩散
DOI：
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复制
发表时间：
2018
影响因子：
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通讯作者：
Christo Wilson
中科院分区：
文献类型：
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作者：
M. Bashir;Christo Wilson
由于在线广告行业向实时竞价（RTB）的转变，广告和分析（A&A）公司已经开始更加紧密地合作。了解用户跟踪数据如何在这个相互关联的广告生态系统中移动的一种自然方法是将其建模为图表。在本文中，我们引入了一种新的图表示，称为包含图，来模拟RTB对广告生态系统中用户跟踪数据扩散的影响。通过对包含图的模拟，我们提供了A&A公司观察到的跟踪信息的上下限估计。我们发现，在合理假设RTB拍卖中的信息共享情况下，52家A&A公司至少观察了普通用户91%的浏览历史记录。我们还评估了拦截策略的有效性（例如AdBlock Plus），并发现主要的A&A公司仍然观察到40-90%的用户印象，这取决于拦截策略。
Abstract Advertising and Analytics (A&A) companies have started collaborating more closely with one another due to the shift in the online advertising industry towards Real Time Bidding (RTB). One natural way to understand how user tracking data moves through this interconnected advertising ecosystem is by modeling it as a graph. In this paper, we introduce a novel graph representation, called an Inclusion graph, to model the impact of RTB on the diffusion of user tracking data in the advertising ecosystem. Through simulations on the Inclusion graph, we provide upper and lower estimates on the tracking information observed by A&A companies. We find that 52 A&A companies observe at least 91% of an average user’s browsing history under reasonable assumptions about information sharing within RTB auctions. We also evaluate the effectiveness of blocking strategies (e.g., AdBlock Plus), and find that major A&A companies still observe 40–90% of user impressions, depending on the blocking strategy.
影响因子：
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作者：
M. Mughees;Zhiyun Qian;Zubair Shafiq
通讯作者：
M. Mughees;Zhiyun Qian;Zubair Shafiq