Title:
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How gender and skin tone modifiers affect emoji semantics in Twitter
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Author:
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Barbieri, Francesco; Camacho-Collados, Jose
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Abstract:
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Comunicació presentada a la Seventh Joint Conference on Lexical and Computational Semantics, celebrada els dies 5 i 6 de juny de 2018 a Nova Orleans, EUA. |
Abstract:
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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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Francesco B. acknowledges support from the TUNER project (TIN2015-65308-C5-5-R, MINECO/FEDER, UE) and the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502). |
Subject(s):
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-Tractament del llenguatge natural (Informàtica) |
Rights:
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© ACL, Creative Commons Attribution 4.0 License.
http://creativecommons.org/licenses/by/4.0/ |
Document type:
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Conference Object Article - Published version |
Published by:
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ACL (Association for Computational Linguistics)
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