Manipulation Robustness of Collaborative Filtering Systems

A collaborative filtering system recommends to users products that similar users like. Collaborative filtering systems influence purchase decisions, and hence have become targets of manipulation by unscrupulous vendors. We provide theoretical and empirical results demonstrating that while common nearest neighbor algorithms, which are widely used in commercial systems, can be highly susceptible to manipulation, two classes of collaborative filtering algorithms which we refer to as linear and asymptotically linear are relatively robust. These results provide guidance for the design of future collaborative filtering systems

How and When Advertising Can Influence Memory for Consumer Experience

Recent paradigm shifting research in consumer behavior dealing with reconstructive memory processes suggests that advertising can exert a powerful retroactive effect on how consumers remember their past experiences with a product. Building on this stream of research, we have executed three studies that incorporate the use of false cues with the aim of shedding new light on how post-experience advertising exerts influence on recollection. Our first experiment investigates an important but yet unexplored issue to advertisers who are perhaps reticent about embracing this paradigm: Does the false cue fundamentally change how consumers process information? After finding that when the false information goes undetected it is processed in a similar manner as more truthful cues, we use this paradigm to shed light on the pictorial versus verbal information debate in advertising. We discuss the implications of our findings for those interested in managing consumer experience and for advertising researchers seeking indirect measures of the influence of advertising