TY - GEN
T1 - Comparison of emoji use in names, profiles, and tweets
AU - Swartz, Melanie
AU - Crooks, Andrew
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/2
Y1 - 2020/2
N2 - Online social networking applications are popular venues for self-expression, communication, and building connections between users. One method of expression is that of emojis, which is becoming more prevalent in online social networking platforms. As emoji use has grown over the last decade, differences in emoji usage by individuals and the way they are used in communication is still relatively unknown. This paper fills this gap by comparing emoji use across users and collectively in user names, profiles, and in original and re-shared content. We present a methodology that enables comparison of semantically similar emojis based on Unicode emoji categories and subcategories. We apply this methodology to a corpus of over 44 million tweets and associated user names and profiles to establish a baseline which reveals differences in emoji use in user names, profile descriptions, non-retweets, and retweets. In addition, our analysis reveals emoji super users who have a significantly higher proportion and diversity of emoji use. Our methodology offers a novel approach for summarizing emoji use and enables systematic comparison of emojis across individual user profiles and communication patterns, thus expanding methods for semantic analysis of social media data beyond just text.
AB - Online social networking applications are popular venues for self-expression, communication, and building connections between users. One method of expression is that of emojis, which is becoming more prevalent in online social networking platforms. As emoji use has grown over the last decade, differences in emoji usage by individuals and the way they are used in communication is still relatively unknown. This paper fills this gap by comparing emoji use across users and collectively in user names, profiles, and in original and re-shared content. We present a methodology that enables comparison of semantically similar emojis based on Unicode emoji categories and subcategories. We apply this methodology to a corpus of over 44 million tweets and associated user names and profiles to establish a baseline which reveals differences in emoji use in user names, profile descriptions, non-retweets, and retweets. In addition, our analysis reveals emoji super users who have a significantly higher proportion and diversity of emoji use. Our methodology offers a novel approach for summarizing emoji use and enables systematic comparison of emojis across individual user profiles and communication patterns, thus expanding methods for semantic analysis of social media data beyond just text.
KW - Content analysis
KW - Emoji
KW - Online social networks
KW - Social media analytics
UR - https://www.scopus.com/pages/publications/85083435170
U2 - 10.1109/ICSC.2020.00075
DO - 10.1109/ICSC.2020.00075
M3 - Conference contribution
AN - SCOPUS:85083435170
T3 - Proceedings - 14th IEEE International Conference on Semantic Computing, ICSC 2020
SP - 375
EP - 380
BT - Proceedings - 14th IEEE International Conference on Semantic Computing, ICSC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE International Conference on Semantic Computing, ICSC 2020
Y2 - 3 February 2020 through 5 February 2020
ER -