TV viewership data available at the individual set-top box level has enabled new methods for estimating the demographics of shows' audiences, but it is impossible to tell with certainty which household members are watching TV in multi-person households. We address this problem through four main...

Dimensionality Reduction (DR) is frequently employed in the predictive modeling process with the goal of improving the generalization performance of models. This paper takes a design science perspective on DR.We treat it as an important business analytics artifact and investigate its utility in...

Crowdfunding campaigns must display authenticity in order to gain potential backers' trust, yet racial minorities may face bias if they include signals of their racial identity in their pages. There are numerous ways that racial identity can be signaled on crowdfunding platforms, and this work...

Digital platforms have a widely-documented issue with bias, which can impact their bottom line via missed opportunities, bad publicity, or even legal action. There is evidence that bias decreases when a platform conveys a signal of quality for underrepresented groups. This paper studies the...

Prediction in financial domains is notoriously difficult for a number ofreasons. First, theories tend to be weak or non-existent, which makesproblem formulation open ended by forcing us to consider a large numberof independent variables and thereby increasing the dimensionality ofthe search...

Prior studies have questioned the degree of anonymity of thedouble-blind review process for scholarly research articles. Forexample, one study based on a survey of reviewers concluded that authorsoften could be identified by reviewers using a combination of theauthor's reference list and the...

Model induction from relational data requires aggregation of values ofattributes of related entities. This paper makes three contributions tothe study of relational learning.(1) It presents a hierarchy ofrelational concepts of increasing complexity, using relational schemacharacteristics such as...

Abstract. In many cost-sensitive environments class probabilityestimates are used by decision makers to evaluate the expected utilityfrom a set of alternatives. Supervised learning can be used to buildclass probability estimates; however, it often is very costly to obtaintraining data with class...

Viral or buzz marketing takes advantage of communication linkages topropagate positive influence regarding a product or service.TelE-commerce is an ideal domain within which to study viral marketing,because communication linkages can be observed. In this paper, we followa new telE-commerce...

This paper is about constructing confidence bands around ROC curves. Wefirst introduce to the machine learning community three band-generatingmethods from the medical field, and evaluate how well they perform. Suchconfidence bands represent the region where the “true” ROCcurve is expected to...