CHS: Medium: Towards Transparency of Personalization on the Web

该项目将开发新的研究方法，绘制和量化在线搜索引擎、社交网络和电子商务网站使用复杂算法为每个用户定制内容的方式。 这种“个性化”通常对用户有价值，但它也有可能扭曲搜索结果并操纵用户的感知和行为。 鉴于个性化在各种基于Web的服务中的流行，这项研究有可能产生极其广泛的影响。 能够量化基于Web的服务的个性化程度将为用户带来更大的透明度，并且开发识别个性化内容的工具将允许用户访问今天可能难以访问的信息。 在许多情况下，个性化为用户提供了优势，因为个性化算法可能返回与用户相关的结果。 与此同时，Web搜索和其他系统中个性化程度的提高导致人们越来越担心过滤器泡沫效应，即用户只能获得个性化算法认为他们想要的结果，而其他重要信息仍然无法访问。 从计算机科学的角度来看，个性化只是一种应用于信息检索和排名问题的工具。 然而，社会学家、哲学家和政治学家认为，个性化可能会导致无意中的审查和“回音室”。“同样，经济学家警告说，无良公司可以利用个性化来引导用户购买价格更高的产品，甚至实施价格歧视，对同一商品向不同用户收取不同的价格。 随着个性化在Web上的普及，很明显，必须开发技术来理解和量化的个性化在各种Web services.This研究有四个主要的推力：（1）开发方法来衡量个性化的移动的内容。 从移动的设备浏览Web的日益普及带来了新的挑战，因为这些设备可以访问用户的地理位置和联系人等敏感内容。 (2)开发系统和技术，用于准确测量大量电子商务网站上几种个性化趋势的流行程度。 最近的传闻证据表明，存在问题的销售策略，包括价格操纵和价格歧视。 (3)开发识别和量化个性化政治内容的技术。(4)衡量财务和健康信息根据位置和社会经济地位个性化的程度。所有这四个重点将开发新的研究方法，这些方法可能在其他研究领域也有效。

This project will develop new research methods to map and quantify the ways in which online search engines, social networks and e-commerce sites use sophisticated algorithms to tailor content to each individual user. This "personalization" may often be of value for the user, but it also has the potential to distort search results and manipulate the perceptions and behavior of the user. Given the popularity of personalization across a variety of Web-based services, this research has the potential for extremely broad impact. Being able to quantify the extent to which Web-based services are personalized will lead to greater transparency for users, and the development of tools to identify personalized content will allow users to access information that may be hard to access today.Personalization is now a ubiquitous feature on many Web-based services. In many cases, personalization provides advantages for users, because personalization algorithms are likely to return results that are relevant to the user. At the same time, the increasing levels of personalization in Web search and other systems are leading to growing concerns over the Filter Bubble effect, where users are only given results that the personalization algorithm thinks they want, while other important information remains inaccessible. From a computer science perspective, personalization is simply a tool that is applied to information retrieval and ranking problems. However, sociologists, philosophers, and political scientists argue that personalization can result in inadvertent censorship and "echo chambers." Similarly, economists warn that unscrupulous companies can leverage personalization to steer users towards higher-priced products, or even implement price discrimination, charging different users different prices for the same item. As the pervasiveness of personalization on the Web grows, it is clear that techniques must be developed to understand and quantify personalization across a variety of Web services.This research has four primary thrusts: (1) To develop methodologies to measure personalization of mobile content. The increasing popularity of browsing the Web from mobile devices presents new challenges, as these devices have access to sensitive content like the user's geolocation and contacts. (2) To develop systems and techniques for accurately measuring the prevalence of several personalization trends on a large number of e-commerce sites. Recent anecdotal evidence has shown instances of problematic sales tactics, including price steering and price discrimination. (3) To develop techniques to identify and quantify personalized political content. (4) To measure the extent to which financial and health information is personalized based on location and socio-economic status. All four of these thrusts will develop new research methodologies that may prove effective in other areas of research as well.