On Measuring Bias in Online Information

Bias in online information has recently become a pressing issue, with search engines, social networks and recommendation services being accused of exhibiting some form of bias. In this vision paper, we make the case for a systematic approach towards measuring bias. To this end, we discuss formal measures for quantifying the various types of bias, we outline the system components necessary for realizing them, and we highlight the related research challenges and open problems.Comment: 6 pages, 1 figur

Pricing strategies by European Low Cost Carriers.

We introduce an on-line pricing tactic where airlines post, at the same time and for the same flight, fares in different currencies that violate the law of One Price. Unexpectedly for an on-line market, we find that price discrimination may be accompanied by arbitrage opportunities and that both tend to persist before a flight’s departure. We find discrimination to be of a competitive type, although arbitrage opportunities are more likely in concentrated routes. Finally, the evidence suggests that discrimination may be used to manage stochastic demand.on-line pricing; price discrimination; Law of One Price; sample selection; dispersion; airlines, exchange rate.

Third Party Tracking in the Mobile Ecosystem

Third party tracking allows companies to identify users and track their behaviour across multiple digital services. This paper presents an empirical study of the prevalence of third-party trackers on 959,000 apps from the US and UK Google Play stores. We find that most apps contain third party tracking, and the distribution of trackers is long-tailed with several highly dominant trackers accounting for a large portion of the coverage. The extent of tracking also differs between categories of apps; in particular, news apps and apps targeted at children appear to be amongst the worst in terms of the number of third party trackers associated with them. Third party tracking is also revealed to be a highly trans-national phenomenon, with many trackers operating in jurisdictions outside the EU. Based on these findings, we draw out some significant legal compliance challenges facing the tracking industry.Comment: Corrected missing company info (Linkedin owned by Microsoft). Figures for Microsoft and Linkedin re-calculated and added to Table

Web Tracking: Mechanisms, Implications, and Defenses

This articles surveys the existing literature on the methods currently used by web services to track the user online as well as their purposes, implications, and possible user's defenses. A significant majority of reviewed articles and web resources are from years 2012-2014. Privacy seems to be the Achilles' heel of today's web. Web services make continuous efforts to obtain as much information as they can about the things we search, the sites we visit, the people with who we contact, and the products we buy. Tracking is usually performed for commercial purposes. We present 5 main groups of methods used for user tracking, which are based on sessions, client storage, client cache, fingerprinting, or yet other approaches. A special focus is placed on mechanisms that use web caches, operational caches, and fingerprinting, as they are usually very rich in terms of using various creative methodologies. We also show how the users can be identified on the web and associated with their real names, e-mail addresses, phone numbers, or even street addresses. We show why tracking is being used and its possible implications for the users (price discrimination, assessing financial credibility, determining insurance coverage, government surveillance, and identity theft). For each of the tracking methods, we present possible defenses. Apart from describing the methods and tools used for keeping the personal data away from being tracked, we also present several tools that were used for research purposes - their main goal is to discover how and by which entity the users are being tracked on their desktop computers or smartphones, provide this information to the users, and visualize it in an accessible and easy to follow way. Finally, we present the currently proposed future approaches to track the user and show that they can potentially pose significant threats to the users' privacy.Comment: 29 pages, 212 reference

Field Experiment Tests for Discrimination against Hispanics in the U.S. Rental Housing Market

This article tests for discrimination against Hispanics in the U.S. rental housing market using e-mail correspondence with landlords advertising units online. We divide Hispanics into two groups: those that appear assimilated into American culture and recent immigrants. We find little difference in the treatment of assimilated Hispanics and whites; however, Hispanics we portray as recent immigrants receive less favorable treatment with margins of net discrimination as large as 6.89% of landlords. We also find discrimination varies significantly at the region level and by the ethnic composition of neighborhoods

Ethnic Discrimination in the Market Place of Small Business Transfers

This paper presents the first field experiment regarding ethnic discrimination in the market place of small business transfers. We let two fictitious prospective buyers, one with a typical Swedish name and one with a typical Arab/Muslim name, respond to advertisements of small business transfers on the Internet in Sweden. We then recorded the number contacts achieved by each fictitious buyer with sellers. We found that sellers discriminated against the buyer with an Arab/Muslim name in the sense that the buyer with an Arab/Muslim name obtained fewer contacts with sellers than did the buyer with a Swedish name.Discrimination, self-employment, small business transfers, ethnic minorities, field experiment.