Search engine and content providers: neutrality, competition and integration

In recent years, there has been a rising concern about the policy of major search engines. The concern comes from search bias, which refers to the ranking of the results of a keyword search on the basis of some other principle than the sheer relevance. This search bias is also named as search non-neutrality. In this paper, we analyse one non-neutral behaviour, that is, a behaviour that results in a search bias: the payment by content providers to the search engine (a.k.a. side payment) in order to improve the chances to be located and accessed by a user. A game theory-based model is presented where a search engine and two content providers interact strategically, while the aggregated behaviour of users is modelled by a demand function. The utility of each stakeholder (i.e. the users, the search engine and each content provider) when the search engine is engaged in such a non-neutral behaviour is compared with that of the neutral case, when no such side payment is present. Additionally, the paper analyses the organisation of such an industry, specifically, the search engine and content providers incentives for a partial and full merger with the content providers, and the effects of each organisation on the users. This paper concludes by identifying the circumstances under which the search bias, on the one hand, and the integration, on the other hand, will effectively result in the users being harmed. This eventual harmful situation will provide a rationale for regulatory measures to be adopted.This work has been supported by the Spanish Ministry of Economy and Competitiveness through project TIN2010-21378-C02-02.Guijarro Coloma, LA.; Pla, V.; Vidal Catalá, JR.; Martínez Bauset, J. (2015). Search engine and content providers: neutrality, competition and integration. Transactions on Emerging Telecommunications Technologies. 26(2):164-178. https://doi.org/10.1002/ett.2827S164178262European Commission Antitrust: commission probes allegations of antitrust violations by google 2010 http://europa.eu/rapid/pressReleasesAction.do?reference=IP/10/1624Manne, G. A., & Wright, J. D. (2011). If Search Neutrality is the Answer, What’s the Question? SSRN Electronic Journal. doi:10.2139/ssrn.1807951Lenard, T. M., & May, R. J. (Eds.). (2006). Net Neutrality or Net Neutering: Should Broadband Internet Services be Regulated. doi:10.1007/0-387-33928-0Altman E Legout A Xu Y Proceedings of IFIP Networking 2011 68 81Ozel, O., & Uysal-Biyikoglu, E. (2012). Network-wide energy efficiency in wireless networks with multiple access points. Transactions on Emerging Telecommunications Technologies, 24(6), 568-581. doi:10.1002/ett.2543Alptekin, G. I., & Bener, A. B. (2011). Spectrum trading in cognitive radio networks with strict transmission power control. European Transactions on Telecommunications, 22(6), 282-295. doi:10.1002/ett.1477Coucheney, P., Maille, P., & Tuffin, B. (2013). Impact of Competition Between ISPs on the Net Neutrality Debate. IEEE Transactions on Network and Service Management, 10(4), 425-433. doi:10.1109/tnsm.2013.090313.120326Coucheney P Maillé P Tuffin B Comparison of search engines non-neutral and neutral behaviors First Workshop on Pricing and Incentives in Networks (W-PIN 2012), Co-located with ACM Sigmetrics/Performance, ACM 2012 1 8Palme E Dellarocas C Calin M Sutanto J Attention allocation in information-rich environments: the case of news aggregators Proceedings of the 14th Annual International Conference on Electronic Commerce, ACM 2012 25 26Guijarro L Pla V Tuffin B Maillé P Coucheney P A game theory-based analysis of search engine non-neutral behavior 2012 8th EURO-NGI Conference on, Next Generation Internet (NGI), IEEE 2012 119 124Singh, N., & Vives, X. (1984). Price and Quantity Competition in a Differentiated Duopoly. The RAND Journal of Economics, 15(4), 546. doi:10.2307/2555525Niyato, D., & Hossain, E. (2008). Competitive Pricing for Spectrum Sharing in Cognitive Radio Networks: Dynamic Game, Inefficiency of Nash Equilibrium, and Collusion. IEEE Journal on Selected Areas in Communications, 26(1), 192-202. doi:10.1109/jsac.2008.080117Jia J Zhang Q Competitions and dynamics of duopoly wireless service providers in dynamic spectrum market Proceedings of the 9th ACM International Symposium on Mobile Ad Hoc Networking and Computing, ACM 2008 313 322Kluberg, J., & Perakis, G. (2012). Generalized Quantity Competition for Multiple Products and Loss of Efficiency. Operations Research, 60(2), 335-350. doi:10.1287/opre.1110.101

Electrophysiological Studies of Visual Attention and of Emotion Regulation

Electrophysiological methods, such as electroencephalography (EEG) and electrocardiography (ECG), measure biological activity that allow us to infer underlying cognitive processes. In the first study, we use EEG to track feature-based attention (FBA), a form of visual attention that helps one detect objects with a particular color, motion, or orientation. We explore the use of SSVEPs, generated by flicker presented peripherally, to track attention in a visual search task presented centrally. Classification results show that one can track an observer’s attended color, which suggests that these methods may provide a viable means for tracking FBA in a real-time task. In the second study, we use cardiovascular measures to examine influences of the emotion regulation strategy of reappraisal. We examine cooperation and cardiovascular responses in individuals that were defected on by their opponent in the first round of an iterated Prisoner’s Dilemma. We find significant differences between the emotion regulation conditions using the biopsychosocial (BPS) model of challenge and threat, where participants primed with the reappraisal strategy were weakly comparable with a threat state of the BPS model and participants without an emotion regulation were weakly comparable with a challenge state of the BPS model. In the third study, we use EEG to study the chromatic sensitivity of FBA for color during a visual search task. We use SSVEP responses evoked through peripheral flicker to measure the spectral tuning of color detection mechanisms and how attentional selection is affected by distractor color. Our results find smaller responses for the distractor colors and suggest that feature-based attention to a particular color involves chromatic mechanisms that both enhance the response to a target and minimize responses to distractors

Pricing average price advertising options when underlying spot market prices are discontinuous

Advertising options have been recently studied as a special type of guaranteed contracts in online advertising, which are an alternative sales mechanism to real-time auctions. An advertising option is a contract which gives its buyer a right but not obligation to enter into transactions to purchase page views or link clicks at one or multiple pre-specified prices in a specific future period. Different from typical guaranteed contracts, the option buyer pays a lower upfront fee but can have greater flexibility and more control of advertising. Many studies on advertising options so far have been restricted to the situations where the option payoff is determined by the underlying spot market price at a specific time point and the price evolution over time is assumed to be continuous. The former leads to a biased calculation of option payoff and the latter is invalid empirically for many online advertising slots. This paper addresses these two limitations by proposing a new advertising option pricing framework. First, the option payoff is calculated based on an average price over a specific future period. Therefore, the option becomes path-dependent. The average price is measured by the power mean, which contains several existing option payoff functions as its special cases. Second, jump-diffusion stochastic models are used to describe the movement of the underlying spot market price, which incorporate several important statistical properties including jumps and spikes, non-normality, and absence of autocorrelations. A general option pricing algorithm is obtained based on Monte Carlo simulation. In addition, an explicit pricing formula is derived for the case when the option payoff is based on the geometric mean. This pricing formula is also a generalized version of several other option pricing models discussed in related studies.Comment: IEEE Transactions on Knowledge and Data Engineering, 201

A Mechanism for Fair Distribution of Resources without Payments

We design a mechanism for Fair and Efficient Distribution of Resources (FEDoR) in the presence of strategic agents. We consider a multiple-instances, Bayesian setting, where in each round the preference of an agent over the set of resources is a private information. We assume that in each of r rounds n agents are competing for k non-identical indivisible goods, (n > k). In each round the strategic agents declare how much they value receiving any of the goods in the specific round. The agent declaring the highest valuation receives the good with the highest value, the agent with the second highest valuation receives the second highest valued good, etc. Hence we assume a decision function that assigns goods to agents based on their valuations. The novelty of the mechanism is that no payment scheme is required to achieve truthfulness in a setting with rational/strategic agents. The FEDoR mechanism takes advantage of the repeated nature of the framework, and through a statistical test is able to punish the misreporting agents and be fair, truthful, and socially efficient. FEDoR is fair in the sense that, in expectation over the course of the rounds, all agents will receive the same good the same amount of times. FEDoR is an eligible candidate for applications that require fair distribution of resources over time. For example, equal share of bandwidth for nodes through the same point of access. But further on, FEDoR can be applied in less trivial settings like sponsored search, where payment is necessary and can be given in the form of a flat participation fee. To this extent we perform a comparison with traditional mechanisms applied to sponsored search, presenting the advantage of FEDoR

SkILL - a Stochastic Inductive Logic Learner

Probabilistic Inductive Logic Programming (PILP) is a rel- atively unexplored area of Statistical Relational Learning which extends classic Inductive Logic Programming (ILP). This work introduces SkILL, a Stochastic Inductive Logic Learner, which takes probabilistic annotated data and produces First Order Logic theories. Data in several domains such as medicine and bioinformatics have an inherent degree of uncer- tainty, that can be used to produce models closer to reality. SkILL can not only use this type of probabilistic data to extract non-trivial knowl- edge from databases, but it also addresses efficiency issues by introducing a novel, efficient and effective search strategy to guide the search in PILP environments. The capabilities of SkILL are demonstrated in three dif- ferent datasets: (i) a synthetic toy example used to validate the system, (ii) a probabilistic adaptation of a well-known biological metabolism ap- plication, and (iii) a real world medical dataset in the breast cancer domain. Results show that SkILL can perform as well as a deterministic ILP learner, while also being able to incorporate probabilistic knowledge that would otherwise not be considered

Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis

Even with impressive advances in automated formal methods, certain problems in system verification and synthesis remain challenging. Examples include the verification of quantitative properties of software involving constraints on timing and energy consumption, and the automatic synthesis of systems from specifications. The major challenges include environment modeling, incompleteness in specifications, and the complexity of underlying decision problems. This position paper proposes sciduction, an approach to tackle these challenges by integrating inductive inference, deductive reasoning, and structure hypotheses. Deductive reasoning, which leads from general rules or concepts to conclusions about specific problem instances, includes techniques such as logical inference and constraint solving. Inductive inference, which generalizes from specific instances to yield a concept, includes algorithmic learning from examples. Structure hypotheses are used to define the class of artifacts, such as invariants or program fragments, generated during verification or synthesis. Sciduction constrains inductive and deductive reasoning using structure hypotheses, and actively combines inductive and deductive reasoning: for instance, deductive techniques generate examples for learning, and inductive reasoning is used to guide the deductive engines. We illustrate this approach with three applications: (i) timing analysis of software; (ii) synthesis of loop-free programs, and (iii) controller synthesis for hybrid systems. Some future applications are also discussed

Internet Advertising and the Generalized Second Price Auction: Selling Billions of Dollars Worth of Keywords

We investigate the "generalized second price" auction (GSP), a new mechanism which is used by search engines to sell online advertising that most Internet users encounter daily. GSP is tailored to its unique environment, and neither the mechanism nor the environment have previously been studied in the mechanism design literature. Although GSP looks similar to the Vickrey-Clarke-Groves (VCG) mechanism, its properties are very different. In particular, unlike the VCG mechanism, GSP generally does not have an equilibrium in dominant strategies, and truth-telling is not an equilibrium of GSP. To analyze the properties of GSP in a dynamic environment, we describe the generalized English auction that corresponds to the GSP and show that it has a unique equilibrium. This is an ex post equilibrium that results in the same payoffs to all players as the dominant strategy equilibrium of VCG.