Binary rating methods are known to allow easier and quicker ratings, yet they do not allow users to express how much they like/dislike an item. In this study, we argue that response times in ratings can be used to gauge the degree or strength of user ratings. We asked users to rate a set of movies while collecting individual response times, confidence levels, and reasons for user ratings. We investigate (1) the possibility of utilizing response time as a way to further distinguish likes and dislikes, and (2) the various factors that affect rating time. We find that response time can be used to distinguish between sure and unsure answers, as well as the mental process users take before rating an item. We believe that our study will be informative to better find user preferences and relations between explicit ratings and implicit data.