Emoji and Self-Identity in Twitter Bios

Jinhang Li, Giorgos Longinos, Steven Wilson, Walid Magdy


Abstract
Emoji are widely used to express emotions and concepts on social media, and prior work has shown that users’ choice of emoji reflects the way that they wish to present themselves to the world. Emoji usage is typically studied in the context of posts made by users, and this view has provided important insights into phenomena such as emotional expression and self-representation. In addition to making posts, however, social media platforms like Twitter allow for users to provide a short bio, which is an opportunity to briefly describe their account as a whole. In this work, we focus on the use of emoji in these bio statements. We explore the ways in which users include emoji in these self-descriptions, finding different patterns than those observed around emoji usage in tweets. We examine the relationships between emoji used in bios and the content of users’ tweets, showing that the topics and even the average sentiment of tweets varies for users with different emoji in their bios. Lastly, we confirm that homophily effects exist with respect to the types of emoji that are included in bios of users and their followers.
Anthology ID:
2020.nlpcss-1.22
Volume:
Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science
Month:
November
Year:
2020
Address:
Online
Editors:
David Bamman, Dirk Hovy, David Jurgens, Brendan O'Connor, Svitlana Volkova
Venue:
NLP+CSS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
199–211
Language:
URL:
https://aclanthology.org/2020.nlpcss-1.22
DOI:
10.18653/v1/2020.nlpcss-1.22
Bibkey:
Cite (ACL):
Jinhang Li, Giorgos Longinos, Steven Wilson, and Walid Magdy. 2020. Emoji and Self-Identity in Twitter Bios. In Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science, pages 199–211, Online. Association for Computational Linguistics.
Cite (Informal):
Emoji and Self-Identity in Twitter Bios (Li et al., NLP+CSS 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.nlpcss-1.22.pdf
Video:
 https://slideslive.com/38940622