Everybody, More or Less, likes Serendipity

Abstract

In the digital era, personalisation systems are the typical way to deal with the massive amount of information on the Web. ese systems decide in our place what we like, possibly hiding us away from a complete world of potentially interesting content. ese systems do not challenge us to open our horizons of interest, trap- ping us more and more in our lter bubble. Introducing diversity and serendipity in the recommendation results has been widely recognised as the solution to this issue in the information retrieval eld. However, serendipity cannot be addressed and measured with traditional accuracy metrics, because it introduces much more complexity in terms of subjectivity and personality. Inspired by the curiosity theory of Berlyne, further developed by Silvia, we introduce in user pro les a so-called coping potential estimation as a measure of the users' ability to cope with new items (e.g., ability to appreciate serendipitous recommendations). Our assumption is that curiosity leads to serendipity and high coping potential users accept more serendipitous results, and thus we need to model it in the recommendation algorithm. We performed an online ex- periment where we asked users a number of questions about TV programmes recommendations. Our results show that users with a high coping potential are more inclined to accept serendipitous recommendations than their counterparts.