  This paper presents an analysis of social experiences around wine consumption
through the lens of Vivino, a social network for wine enthusiasts with over 26
million users worldwide. We compare users' perceptions of various wine types
and regional styles across both New and Old World wines, examining them across
price ranges, vintages, regions, varietals, and blends. Among other things, we
find that ratings provided by Vivino users are not biased by cost. We then
study how wine characteristics, language in wine reviews, and the distribution
of wine ratings can be combined to develop prediction models. More
specifically, we model user behavior to develop a regression model for
predicting wine ratings, and a classifier for determining user review
preferences.
