Through a Gender Lens: Learning Usage Patterns of Emojis from Large Scale Android Users
Based on a large data set of emoji using behavior collected from smartphone users over the world, this paper investigates gender specific usage of emojis. We present various interesting findings that evidence a considerable difference in emoji usage by female and male 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 textual or contextual information. Emojis not only provide language independent indicators, but also alleviate the risk of leaking private user information through the analysis of text and metadata.
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