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        <title>How Gender and Skin Tone Modifiers Affect Emoji Semantics in Twitter</title>
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            <namePart type="given">Malvina</namePart>
            <namePart type="family">Nissim</namePart>
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    <abstract>In this paper we analyze the use of emojis in social media with respect to gender and skin tone. By gathering a dataset of over twenty two million tweets from United States some findings are clearly highlighted after performing a simple frequency-based analysis. Moreover, we carry out a semantic analysis on the usage of emojis and their modifiers (e.g. gender and skin tone) by embedding all words, emojis and modifiers into the same vector space. Our analyses reveal that some stereotypes related to the skin color and gender seem to be reflected on the use of these modifiers. For example, emojis representing hand gestures are more widely utilized with lighter skin tones, and the usage across skin tones differs significantly. At the same time, the vector corresponding to the male modifier tends to be semantically close to emojis related to business or technology, whereas their female counterparts appear closer to emojis about love or makeup.</abstract>
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%0 Conference Proceedings
%T How Gender and Skin Tone Modifiers Affect Emoji Semantics in Twitter
%A Barbieri, Francesco
%A Camacho-Collados, Jose
%Y Nissim, Malvina
%Y Berant, Jonathan
%Y Lenci, Alessandro
%S Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F barbieri-camacho-collados-2018-gender
%X In this paper we analyze the use of emojis in social media with respect to gender and skin tone. By gathering a dataset of over twenty two million tweets from United States some findings are clearly highlighted after performing a simple frequency-based analysis. Moreover, we carry out a semantic analysis on the usage of emojis and their modifiers (e.g. gender and skin tone) by embedding all words, emojis and modifiers into the same vector space. Our analyses reveal that some stereotypes related to the skin color and gender seem to be reflected on the use of these modifiers. For example, emojis representing hand gestures are more widely utilized with lighter skin tones, and the usage across skin tones differs significantly. At the same time, the vector corresponding to the male modifier tends to be semantically close to emojis related to business or technology, whereas their female counterparts appear closer to emojis about love or makeup.
%R 10.18653/v1/S18-2011
%U https://aclanthology.org/S18-2011
%U https://doi.org/10.18653/v1/S18-2011
%P 101-106

Markdown (Informal)

[How Gender and Skin Tone Modifiers Affect Emoji Semantics in Twitter](https://aclanthology.org/S18-2011) (Barbieri & Camacho-Collados, *SEM 2018)

• How Gender and Skin Tone Modifiers Affect Emoji Semantics in Twitter (Barbieri & Camacho-Collados, *SEM 2018)

ACL

• Francesco Barbieri and Jose Camacho-Collados. 2018. How Gender and Skin Tone Modifiers Affect Emoji Semantics in Twitter. In Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics, pages 101–106, New Orleans, Louisiana. Association for Computational Linguistics.