Title: Self-authored interest profiles for personalised recommendations

Authors: Reuben Binns

Addresses: Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK

Abstract: A large portion of the content, recommendations and advertisements shown on the web are targeted, based on a profile of an individual user. This paper explores two ways of creating and using such profiles. Behavioural profiling - a commonly used technique which makes inferences based on an individual's previous activity - is compared to what I call Self-Authored Interest (SAI) profiling, which is based on information explicitly volunteered and controlled by the individual. I present the results of an experimental study comparing the effectiveness of the two systems in generating targeted product recommendations. I find that (a) people respond more positively to product recommendations when they are derived from SAI profiles, and (b) the mere belief that a recommendation comes from an SAI profile is also associated with more positive responses.

Keywords: digital marketing; behavioural profiling; behavioural targeting; privacy; recommender systems; uncanny valley; permission marketing; vendor relationship management; personal data; personalisation; self-authoring; personalised recommendations.

DOI: 10.1504/IJIMA.2016.080168

International Journal of Internet Marketing and Advertising, 2016 Vol.10 No.3, pp.207 - 222

Received: 26 Mar 2015
Accepted: 20 Apr 2016
Published online: 06 Nov 2016 *

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