TY - GEN
T1 - #SupportTheCause
T2 - Conference on Empirical Methods in Natural Language Processing, EMNLP 2015
AU - Nguyen, Dong
AU - Van Den Broek, Tijs
AU - Hauff, Claudia
AU - Hiemstra, Djoerd
AU - Ehrenhard, Michel
PY - 2015/1/1
Y1 - 2015/1/1
N2 - We consider the task of automatically identifying participants' motivations in the public health campaign Movember and investigate the impact of the different motivations on the amount of campaign donations raised. Our classification scheme is based on the Social Identity Model of Collective Action (van Zomeren et al., 2008). We find that automatic classification based on Movember profiles is fairly accurate, while automatic classification based on tweets is challenging. Using our classifier, we find a strong relation between types of motivations and donations. Our study is a first step towards scaling-up collective action research methods.
AB - We consider the task of automatically identifying participants' motivations in the public health campaign Movember and investigate the impact of the different motivations on the amount of campaign donations raised. Our classification scheme is based on the Social Identity Model of Collective Action (van Zomeren et al., 2008). We find that automatic classification based on Movember profiles is fairly accurate, while automatic classification based on tweets is challenging. Using our classifier, we find a strong relation between types of motivations and donations. Our study is a first step towards scaling-up collective action research methods.
UR - http://www.scopus.com/inward/record.url?scp=84959905894&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84959905894&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84959905894
T3 - Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing
SP - 2570
EP - 2576
BT - Conference Proceedings - EMNLP 2015
PB - Association for Computational Linguistics (ACL)
Y2 - 17 September 2015 through 21 September 2015
ER -