A Comparative Analysis of Personality-Based Music Recommender Systems Melissa Onori Department of Engineering Roma Tre University Via della Vasca Navale, 79 00146 Rome, Italy melissa.onori@gmail.com Alessandro Micarelli Department of Engineering Roma Tre University Via della Vasca Navale, 79 00146 Rome, Italy micarel@dia.uniroma3.it Giuseppe Sansonetti Department of Engineering Roma Tre University Via della Vasca Navale, 79 00146 Rome, Italy gsansone@dia.uniroma3.it ABSTRACT This article describes a preliminary study on considering in- formation about the target user’s personality in music rec- ommender systems (MRSs). For this purpose, we devised and implemented four MRSs and evaluated them on a sam- ple of real users and real-world datasets. Experimental re- sults show that MRSs that rely on purely users’ personal- ity information are able to provide performance comparable with those of a state-of-the-art MRS, even better in terms of the diversity of the suggested items. Keywords Personality; music recommendation; evaluation 1. INTRODUCTION Music plays an important role in entertainment and leisure of human beings. With the advent of Web 2.0, a huge amount of music content has been made available to millions of people around the world. This has provided new oppor- tunities for researchers working on music information with the aim of creating new services that support navigation, discovery, sharing, and the development of online communi- ties among users. Music recommender systems (MRSs) aim to predict what people like to listen to. A recent research field in music recommendation explores the possibility of harnessing information on the target user’s personality in the recommendation process. The goal of the research work described in this paper is to assess the potential benefits of such integration. To this end, we implemented and compared with each other different MRSs, three of them based on users’ personality inferred from explicit and implicit feedbacks, and one that does not consider users’ personality. 2. RELATED WORK In the research literature, there exist several works that EMPIRE 2016, September 16, 2016, Boston, MA, USA. Copyright held by the author(s). reveal how information about a user’s personality can help infer her music preferences and contribute to a more accu- rate recommendation process [31]. Therefore, several note- worthy MRSs considering the active user’s personality have been proposed. Among others, Ferwerda and Schedl [12] propose an approach where users’ personality and emotional states are implicitly extracted by analyzing their microblogs on Twitter. The authors make use of the extraction tech- niques described by Golbeck [14] and Quercia et al. [30], also trying to combine them for better predictions. Hu and Pu [18] compare a personality test-based MRS with a classic rating-based one. The authors point out that users are more inclined to results returned from the former. According to Hu and Pu, the active user perceives less effort and less time to use the personality test-based MRS. They further claim that users show a strong intention to use such MRS again and an unexpected surprise in its results, as they feel that the personality-based approach is able to reveal their hidden preferences, thereby improving the recommendation process. Also Tkal˘ ci˘ c et al. [34] show that recommenders based on Big Five data can outperform rating-based recom- menders. In [19], Hu and Pu consider again their previous results, exploring the use of personality tests for creating psychological profiles of user’s friends as well. They enable the MRS to generate recommendations for users and their friends too. They also suggest that personality-based MRSs are preferred by no music connoisseurs, which do not know their music preferences in depth. 3. PERSONALITY Generally speaking, an individual’s personality can be de- fined as a combination of characteristics and qualities that make up the way she thinks, feels, and behaves in different situations [33]. Personality and emotions shape our every- day life, having a strong influence on our tastes [32], deci- sions [29], purchases [6], and general behavior [7]. It has been shown that people with similar personalities turn out to have similar preferences [8]. However, giving a more rigor- ous definition of personality can be challenging, so different theories have been formulated to specifically make easier the comprehension of self and others [9]. Each of these theories differently addresses the problem of representing and charac- terizing the human personality. We are interested in theories that would allow us to differentiate people from each other through measurable traits. The subject of the psychology of personality traits is the study of the psychological differ- ences between individuals and relies on empirical research.