The Effect of Relational versus Anecdotal Explanations in Movie Domain Recommendations

This paper explores the effect explanation type has on people’s perceptions of recommendation quality. More specifically, we explore this effect in systems whose users ‘consume’ an entity by reading about the entity. In such systems, one of the main goals is to persuade the user to extend their exploration of the domain. We compare two explanation types: relational explanations and anecdotal explanations. We compare them in the movie domain using a between-subject study. We use Path Analysis (PA) to evaluate our results. We find that using anecdotal explanations positively affects how informative and entertaining participants find explanations, which, in turn, positively impacts how interesting the user finds the explanation. Finally, this positively affects the perceived quality of the recommendations. We also explore the impact a user’s level of domain engagement has on these factors. We find that it positively correlates with how interesting they perceive the explanations to be and with the perceived recommendation quality.