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This article explores gender roles and gender displays in animated GIFs. The 747 most popular reaction GIFs accessible via Tenor, Giphy, and Gfycat were content analyzed. An automated approach using machine learning and a human coding approach were used to code for primary characters. Findings revealed that female characters were underrepresented in comparison to their counterparts. Across the age groups, women appeared younger than men. Compared with male figures, females were more prone to be portrayed as slightly nude, wearing sexually revealing clothing, and sometimes in attire considered unsuitable for the context of the situation. In contrast, chi-square analyses indicated no significant differences between genders in terms of nonverbal behaviors (“displays”) such as expression of emotions, smiling, or gazing, and use of gestures. The results of sentiment analysis in reaction GIFs’ titles showed no different sentiment scores for GIFs depicting either male or female main characters. [ABSTRACT FROM AUTHOR]