TY - JOUR
T1 - Twitter data for predicting election results
T2 - Insights from emotion classification
AU - Srinivasan, Satish M.
AU - Sangwan, Raghvinder S.
AU - Neill, Colin J.
AU - Zu, Tianhai
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - The advent of social media and microblogging sites has paved the way for individuals and communities to freely express their opinions, feelings, and thoughts on a variety of topics in the form of short and limited size texts such as tweets. These tweets can hold a wealth of information on how individuals communicate their thoughts, emotions (happiness, anxiety, depression, etc.) and feelings within their social network [1].
AB - The advent of social media and microblogging sites has paved the way for individuals and communities to freely express their opinions, feelings, and thoughts on a variety of topics in the form of short and limited size texts such as tweets. These tweets can hold a wealth of information on how individuals communicate their thoughts, emotions (happiness, anxiety, depression, etc.) and feelings within their social network [1].
UR - http://www.scopus.com/inward/record.url?scp=85062964081&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062964081&partnerID=8YFLogxK
U2 - 10.1109/MTS.2019.2894472
DO - 10.1109/MTS.2019.2894472
M3 - Article
AN - SCOPUS:85062964081
SN - 0278-0097
VL - 38
SP - 58
EP - 63
JO - IEEE Technology and Society Magazine
JF - IEEE Technology and Society Magazine
IS - 1
M1 - 8664560
ER -