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Based on a large data set of emoji using behavior collected from smartphoneusers over the world, this paper investigates gender-specific usage of emojis.We present various interesting findings that evidence a considerable differencein emoji usage by female and male users. Such a difference is significant notjust in a statistical sense; it is sufficient for a machine learning algorithmto accurately infer the gender of a user purely based on the emojis used intheir messages. In real world scenarios where gender inference is a necessity,models based on emojis have unique advantages over existing models that arebased on textual or contextual information. Emojis not only providelanguage-independent indicators, but also alleviate the risk of leaking privateuser information through the analysis of text and metadata.

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