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

## TL;DR

This paper introduces a social sensing method using Foursquare check-in data to analyze and compare gender preferences for venues across different regions worldwide, revealing cultural patterns efficiently.

## Contribution

It presents a novel, scalable approach to studying gender preferences for venues using social sensing data, reducing reliance on costly traditional surveys.

## Key findings

- Significant gender-based differences in venue preferences across regions.
- Method captures known cultural gender patterns.
- Approach is faster and cheaper than traditional surveys.

## Abstract

Gender differences is a phenomenon around the world actively researched by social scientists. Traditionally, the data used to support such studies is manually obtained, often through surveys with volunteers. However, due to their inherent high costs because of manual steps, such traditional methods do not quickly scale to large-size studies. We here investigate a particular aspect of gender differences: preferences for venues. To that end we explore the use of check-in data collected from Foursquare to estimate cultural gender preferences for venues in the physical world. For that, we first demonstrate that by analyzing the check-in data in various regions of the world we can find significant differences in preferences for specific venues between gender groups. Some of these significant differences reflect well-known cultural patterns. Moreover, we also gathered evidence that our methodology offers useful information about gender preference for venues in a given region in the real world. This suggests that gender and venue preferences observed may not be independent. Our results suggests that our proposed methodology could be a promising tool to support studies on gender preferences for venues at different spatial granularities around the world, being faster and cheaper than traditional methods, besides quickly capturing changes in the real world.