Abstract—Recent years have witnessed incredible growth in the popularity and prevalence of smart phones. A flourishing mobile application market has evolved to provide users with additional functionality such as interacting with social networks, games, and more. Mobile applications may have a direct purchasing cost or be free but ad-supported. Unlike in-browser ads, the privacy implications of ads in Android applications has not been thoroughly explored. We start by comparing the similarities and differences of in-browser ads and in-app ads. We examine the effect on user privacy of thirteen popular Android ad providers by reviewing their use of permissions. Worryingly, several ad libraries checked for permissions beyond the required and optional ones listed in their documentation, including dangerous permissions like CAMERA, WRITE CALENDAR and WRITE CONTACTS. Further, we discover the insecure use of Android’s JavaScript extension mechanism in several ad libraries. We identify fields in ad requests for private user information and confirm their presence in network data obtained from a tier-1 network provider. We also show that users can be tracked by a network sniffer across ad providers and by an ad provider across applications. Finally, we discuss several possible solutions to the privacy issues identified above. I.

Online customer data are used by advertisers and marketers to target their marketing appeals. This has heightened consumers ’ privacy concerns, leading governments to pass laws designed to protect consumer privacy by restricting the use of data and by restricting online tracking techniques used by websites. We use an expansive database of field studies for online display (banner) advertising to explore how European privacy regulation has influenced advertising effectiveness. We find that display advertising became far less effective at changing stated purchase intent after the laws were enacted. The loss in effectiveness was more pronounced for websites that had general content (such as news sites), where non-data-driven targeting is particularly hard to do. The loss of effectiveness was also more pronounced for ads with a smaller page presence and for ads that did not have additional interactive, video, or audio features.

In this paper, we explore the hypothesis that an important force behind the collapse in advertising revenue experienced by newspapers in the past decade is the greater consumer switching facilitated by online consumption of news. We introduce a model of the market for advertising on news media outlets whereby news outlets are modeled as competing two-sided platforms bringing together heterogeneous, partially multi-homing consumers with advertisers with heterogeneous valuations for reaching consumers. A key feature of our model is that the multi-homing behavior of the advertisers is determined endogenously. The presence of switching consumers means that, in the absence of perfect technologies for tracking the ads seen by consumers, advertisers purchase wasted impressions: they reach the same consumer too many times. This has subtle effects on the equilibrium outcomes in the advertising market. One consequence is that multi-homing on the part of advertisers is heterogeneous: high-value advertisers multi-home, while low-value advertisers single-home. We characterize the impact of greater consumer switching on outlet profits as well as the impact of technologies that track consumers both within and across outlets on those profits. Somewhat surprisingly, superior tracking technologies may not always increase outlet profits, even when they increase efficiency. In extensions to the baseline model, we show that when

Advertising is one of the primary means for revenue generation for millions of websites and mobile apps. While the majority of online advertising revenues are based on payper-click, alternative forms such as impression-based display and video advertising have been growing rapidly over the past several years. In this paper, we investigate the problem of invalid traffic generation that aims to inflate advertising impressions on websites. Our study begins with an analysis of purchased traffic for a set of honeypot websites. Data collected from these sites provides a window into the basic mechanisms used for impression fraud and in particular enables us to identify pay-per-view (PPV) networks. PPV networks are comprised of legitimate websites that use JavaScript provided by PPV network service providers to render unwanted web pages "underneath " requested content on a real user’s browser so that additional advertising impressions are registered. We describe the characteristics of the PPV network ecosystem and the typical methods for delivering fraudulent impressions. We also provide a case study of scope of PPV networks in the Internet. Our results show that these networks deliver hundreds of millions of fraudulent impressions per day, resulting in hundreds of millions of lost advertising dollars annually. Characteristics unique to traffic delivered via PPV networks are also discussed. We conclude with recommendations for countermeasures that can reduce the scope and impact of PPV networks. 1.

This article investigates the role of a search engine as an intermediary between firms and consumers. Search engines enable firms to target consumers who have revealed some specific needs through their query. In a framework with horizontal product differentiation, imperfect product information and in which consumers incur search costs, I show that introducing a mechanism which enables firms to target consumers reduces social inefficiencies but has ambiguous effects on the equilibrium price. A profit maximizing search engine has incentives to design the mechanism so as to soften price competition between firms, in order to extract profit from them, and this may not be socially efficient. Sufficient conditions for efficiency of the outcome are provided.

Many two-sided platforms (such as search engines and business directories) make profits from auctioning their user base to advertisers. Yet, auctioning users is different from selling standard commodities, since the participation decision by users (and, therefore, the size of the platform’s user base) depends on the benefit users expect to receive from joining the platform. In this setting, what is the profit-maximizing auction? And how should a platform structure its user fees? First, I show that if bidders profit from the match more than users, it is optimal for the platform to offer subsidies to users, and recoup losses on the user side of the market by inducing aggressive bidding on the bidder side (loss leader strategy). Second, I show that if the bidders’ willingness to pay for the match is positively affiliated with the value users derive from bidders, the revenue-maximizing mechanism favors bidders with low values to users (search diversion). In turn, when charging or subsidizing users is not feasible, the platform favors bidders with high (low) user values as a substitute for the subsidies (fees) it would otherwise implement. In this setting, I also show that competition between two-sided platforms can decrease total welfare when the supply of users is sufficiently inelastic. This result implies that applying standard antitrust economics to two-sided markets may be misleading.

When people go on the web, they surf. Accordingly, in many circumstances, such as when people use a search engine (SE) to find a “content website ” (CW), such pairs of websites are complements. Typically, both of these types of sites show advertisements to their visitors, but they do so using very different technologies. We study the incentives for such ad-funded websites with differing technologies to force their visitors to pay attention by putting up with distracting advertisements. We show that SEs and CWs face two distinct coordination problems when designing their advertising strategies. The first is the classic problem of double marginalization among sellers of complements. The second potential problem is new: the need to efficiently allocate demands to a given user for her attention. Because of this second issue, the market for user attention exhibits surprising behavior when competition increases. In particular, heightened competition among sites of a given type (SE or CW) may cause social welfare to decrease by giving the other type of site incentive to make more inefficient demands for the users ’ attention.

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We study the market for applications on Facebook, the dominant platform for social networking and make use of a rule change by Facebook by which high-quality applications were rewarded with further opportunities to engage users. We find that the change led to quality being a more important driver of usage while sheer network size became less important. Further, we find that update frequency helps applications maintain higher usage, while generally usage of Facebook applications declines less rapidly with age.

This paper investigates the optimal design of advertising auctions such as those used by search engines to sell space to advertisers. A key feature of these auctions is that the value of the advertising position depends on the searchers’ expectation that the selected advertiser is relevant to their needs. The revenue-maximizing mechanism is a scoring auction that works as a crosss-ubsidization device between searchers and advertisers. Relative to efficiency, profit-maximization selects lower quality advertisers, and searchers make fewer clicks. The implications for competition policy are subtle. Circumstances are characterized in which an increase in competition between auction platforms decreases welfare.