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Gender differences is a phenomenon around the world actively researched bysocial scientists. Traditionally, the data used to support such studies ismanually obtained, often through surveys with volunteers. However, due to theirinherent high costs because of manual steps, such traditional methods do notquickly scale to large-size studies. We here investigate a particular aspect ofgender differences: preferences for venues. To that end we explore the use ofcheck-in data collected from Foursquare to estimate cultural gender preferencesfor venues in the physical world. For that, we first demonstrate that byanalyzing the check-in data in various regions of the world we can findsignificant differences in preferences for specific venues between gendergroups. Some of these significant differences reflect well-known culturalpatterns. Moreover, we also gathered evidence that our methodology offersuseful information about gender preference for venues in a given region in thereal world. This suggests that gender and venue preferences observed may not beindependent. Our results suggests that our proposed methodology could be apromising tool to support studies on gender preferences for venues at differentspatial granularities around the world, being faster and cheaper thantraditional methods, besides quickly capturing changes in the real world.

Gender Matters! Analyzing Global Cultural Gender Preferences for Venues Using Social Sensing