TY - GEN
T1 - Differences in emoji sentiment perception between readers and writers
AU - Berengueres, Jose
AU - Castro, Dani
PY - 2017/7/1
Y1 - 2017/7/1
N2 - Previous research has traditionally analyzed emoji sentiment from the point of view of the reader of the content not the author. Here, we analyze emoji sentiment from the point of view of the author and present an emoji sentiment benchmark that was built from an employee happiness dataset where emoji happen to be annotated with daily happiness of the author of the comment. The data spans over 3 years, and 4k employees of 56 companies based in Barcelona. We compare sentiment of writers to readers. Results indicate that, there is an 82% agreement in how emoji sentiment is perceived by readers and writers. The disagreement concentrates in negative emoji, where the authors report to feel 26% worse than perceived by readers. Emoji use was not found to be correlated with author moodiness. Authors that use emoji are happier than authors that never use emoji.
AB - Previous research has traditionally analyzed emoji sentiment from the point of view of the reader of the content not the author. Here, we analyze emoji sentiment from the point of view of the author and present an emoji sentiment benchmark that was built from an employee happiness dataset where emoji happen to be annotated with daily happiness of the author of the comment. The data spans over 3 years, and 4k employees of 56 companies based in Barcelona. We compare sentiment of writers to readers. Results indicate that, there is an 82% agreement in how emoji sentiment is perceived by readers and writers. The disagreement concentrates in negative emoji, where the authors report to feel 26% worse than perceived by readers. Emoji use was not found to be correlated with author moodiness. Authors that use emoji are happier than authors that never use emoji.
KW - Emoji
KW - Happiness
KW - Sentiment
UR - http://www.scopus.com/inward/record.url?scp=85047756992&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85047756992&partnerID=8YFLogxK
U2 - 10.1109/BigData.2017.8258461
DO - 10.1109/BigData.2017.8258461
M3 - Conference contribution
AN - SCOPUS:85047756992
T3 - Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
SP - 4321
EP - 4328
BT - Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
A2 - Nie, Jian-Yun
A2 - Obradovic, Zoran
A2 - Suzumura, Toyotaro
A2 - Ghosh, Rumi
A2 - Nambiar, Raghunath
A2 - Wang, Chonggang
A2 - Zang, Hui
A2 - Baeza-Yates, Ricardo
A2 - Baeza-Yates, Ricardo
A2 - Hu, Xiaohua
A2 - Kepner, Jeremy
A2 - Cuzzocrea, Alfredo
A2 - Tang, Jian
A2 - Toyoda, Masashi
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE International Conference on Big Data, Big Data 2017
Y2 - 11 December 2017 through 14 December 2017
ER -