Through a Gender Lens: Learning Usage Patterns of Emojis from Large-Scale Android Users

Based on a large dataset of emoji usage collected from smartphone users across the world, this paper investigates usage of emojis from the gender perspective. We present various interesting findings that evidence a considerable difference in emoji usage between male and female users. Such a difference is significant not just in a statistical sense; it is sufficient for a machine learning algorithm to accurately infer the gender of a user purely based on the emojis used in their messages. In real-world scenarios where gender inference is a necessity, models based on emojis have unique advantages over existing models that are based on the textual or contextual information. Emojis not only provide the language-independent indicator, but also alleviate the risk of leaking private user information through the analysis of text and context.