Off-Policy Evaluation of Probabilistic Identity Data in Lookalike Modeling

We evaluate the impact of probabilistically-constructed digital identity data collected from Sep. to Dec. 2017 (approx.), in the context of Lookalike-targeted campaigns. The backbone of this study is a large set of probabilistically-constructed "identities", represented as small bags of cookies and mobile ad identifiers with associated metadata, that are likely all owned by the same underlying user. The identity data allows to generate "identity-based", rather than "identifier-based", user models, giving a fuller picture of the interests of the users underlying the identifiers. We employ off-policy techniques to evaluate the potential of identity-powered lookalike models without incurring the risk of allowing untested models to direct large amounts of ad spend or the large cost of performing A/B tests. We add to historical work on off-policy evaluation by noting a significant type of "finite-sample bias" that occurs for studies combining modestly-sized datasets and evaluation metrics involving rare events (e.g., conversions). We illustrate this bias using a simulation study that later informs the handling of inverse propensity weights in our analyses on real data. We demonstrate significant lift in identity-powered lookalikes versus an identity-ignorant baseline: on average ~70% lift in conversion rate. This rises to factors of ~(4-32)x for identifiers having little data themselves, but that can be inferred to belong to users with substantial data to aggregate across identifiers. This implies that identity-powered user modeling is especially important in the context of identifiers having very short lifespans (i.e., frequently churned cookies). Our work motivates and informs the use of probabilistically-constructed identities in marketing. It also deepens the canon of examples in which off-policy learning has been employed to evaluate the complex systems of the internet economy.Comment: Accepted by WSDM 201

Datamining for Web-Enabled Electronic Business Applications

Web-Enabled Electronic Business is generating massive amount of data on customer purchases, browsing patterns, usage times and preferences at an increasing rate. Data mining techniques can be applied to all the data being collected for obtaining useful information. This chapter attempts to present issues associated with data mining for web-enabled electronic-business

Product Fuzzy Recommendation of Online Reviews Based on Consumer Psychological Motives

Sentiment analysis of online comments and their application has become a hot topic. Meanwhile the evaluation and emotion method has challenged researchers and practitioners. This paper proposes a fuzzy modeling for the evaluation and emotion of online review texts by means of the theory of consumption motivation type and establishes corresponding fuzzy corpus. A calculation method of comprehensive evaluation and emotion with respect to the consumer‟s preference for product attributes provide reasoning antecedents. Establishment of fuzzy inference rules give results of recommendation to consumers of four different motivations. Experimental results prove the validity of the proposed method

Extracting Business Intelligence from Online Product Reviews: An Experiment of Automatic Rule-Induction

Online product reviews are a major source of business intelligence (BI) that helps managers and market researchers make important decisions on product development and promotion. However, the large volume of online product review data creates significant information overload problems, making it difficult to analyze users’ concerns. In this paper, we employ a design science paradigm to develop a new framework for designing BI systems that correlate the textual content and the numerical ratings of online product reviews. Based on the framework, we developed a prototype for extracting the relationship between the user ratings and their textual comments posted on Amazon.com’s Web site. Two data mining algorithms were implemented to extract automatically decision rules that guide the understanding of the relationship. We report on experimental results of using the prototype to extract rules from online reviews of three products and discuss the managerial implications

Delivering due process and procedural efficiency at low cost: The grail quest of international online arbitration

This is the author accepted manuscript. The final version is available from the publisher via the link in this recordDesigning an online arbitration procedure which delivers the cornerstone requirements of efficiency, value and fairness has been described as the ‘grail quest’ for online dispute resolution (ODR). Focusing on the incipient global legal framework for both business-to-consumer (B2C) and business-to-business (B2B) arbitration, this paper explores whether current due process or consumer protection laws might be preventing the creation of an international system of binding low-value online ODR. Intending to stimulate innovation in this nascent industry, evaluation is made of the unsuccessful efforts to develop a transnational online arbitration model at the United Nations Commission on Trade Law, the newly launched European Union online dispute resolution platform, and the extant Uniform Domain Name Dispute Resolution Policy. Through comparison of EU and US approaches to mandatory consumer arbitration clauses, it questions whether such clauses would need to become enforceable ex ante before an international consumer arbitration system can ever be fully fledged. It also explores the minimum procedural requirements for low-value B2B and B2C arbitration and, as such, may be of great interest to dispute resolution entrepreneurs, professionals and regulators wishing to capitalise on the growing millions of high-volume low-value cross-border legal claims not being internally managed by online intermediaries or service providers. By reviewing various developments in the industry, such as fast-track arbitration and consumer ODR systems, it will attempt to resolve the ever-present dilemma of maintaining each fairness and efficiency within an affordable and expedient online arbitration process. Naturally, therefore, various elements of online arbitration procedural design are closely examined, appraising matters such as documents-only hearings, fees & funding, document disclosure, time limits, transparency, award reasoning and applicable law

Rebuilding Corporate Leadership: How Directors Can Link Long-Term Performance with Public Goals

This report examines how efforts to build public trust and long-term value have coalesced to encourage many large, global corporations to pay greater attention to their longer-term interests by striking a balance between short-term commercial pursuits and such societal concerns as the environment, labor standards, and human rights. Many companies have also found ways to turn such concerns as the effects of climate change and other environmental damage into profitable commercial opportunities. This report also explores how all corporate boards could take a more active part in considering such issues and improving the reporting of financial and non-financial measures of corporate performance broadly conceived. In our view, directors could do more with their current authority to motivate managements to greater innovation, and to support managements in finding long-term value solutions to the numerous economic and societal pressures they face

A data mining approach for developing online streaming recommendations

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Semantic annotation of digital music

AbstractIn recent times, digital music items on the internet have been evolving in a vast information space where consumers try to find/locate the piece of music of their choice by means of search engines. The current trend of searching for music by means of music consumersʼ keywords/tags is unable to provide satisfactory search results. It is argued that search and retrieval of music can be significantly improved provided end-usersʼ tags are associated with semantic information in terms of acoustic metadata – the latter being easy to extract automatically from digital music items. This paper presents a lightweight ontology that will enable music producers to annotate music against MPEG-7 description (with its acoustic metadata) and the generated annotation may in turn be used to deliver meaningful search results. Several potential multimedia ontologies have been explored and a music annotation ontology, named mpeg-7Music, has been designed so that it can be used as a backbone for annotating music items

Framing the Facebook Oversight Board: Rough Justice in the Wild Web?

L'articolo analizza la struttura del Facebook Oversight Board e i problemi connessi con la costituzione di giurisdizioni private, interne agli ISP, anche alla luce del DSA della U