Author Archives: Raghav

Different Strokes for Different Folks: The Value of Personality Type in Recommender Systems and Social Computing

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Did you know that your personality type can be used to predict your behavior on an online recommender site (how long you stay, what you do, whether and how much you are likely to rate)  and even what to recommend to you? That’s what we found in our latest research using the MovieLens recommender system and the Big Five Personality scale for modeling user personality. To learn more, read on!

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The more they try, the more they are likely to come back!!

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Are you trying to launch an online site for customers? Did you know that on an average, 60% of users do not return to a site after their first visit?

In this research, we discover factors that predict whether first-time users return to MovieLens, our movie recommendation site.  A model based on these factors successfully predicts 70% of returning users (and non-returning ones).  Notably, the best single predictor of user return is the diversity of features explored in the user’s first session!  Along the way, we develop a process and a metric for activity diversity — one that can be applied to any site or context. Interested in further details? Read on!

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