Emoji are Effective Predictors of User’s Demographics
Pages 784 - 792
Abstract
Social media platforms like Twitter provide rich data that can offer insights into various aspects of users' behavior. In this study, we explore the potential of emoji usage as a means for demographic prediction. Leveraging a Twitter dataset of 18,689 users, annotated with gender and ethnicity labels, we analyze the proportion of tweets containing emoji across different demographic groups. We identify significant variations in emoji usage, with women utilizing emoji more frequently than men and users of African descent displaying a higher tendency for emoji usage compared to users of European descent. Moreover, we investigate the most distinctive emoji for each group, revealing intriguing patterns that are closely tied to the cultural and demographic backgrounds of users. Building upon these findings, we employ machine learning models with different feature extraction techniques to predict users' gender and ethnicity. Our results demonstrate the predictive power of emoji, outperforming traditional text-based features. Furthermore, our study provides evidence that emoji usage can be a valuable resource for inferring user demographic characteristics on social media platforms, contributing to our understanding of user behavior in digital environments.
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Index Terms
- Emoji are Effective Predictors of User’s Demographics
Index terms have been assigned to the content through auto-classification.
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Published: 15 March 2024
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