#SupportTheCause: Identifying motivations to participate in online health campaigns

Dong Nguyen, Tijs Van Den Broek, Claudia Hauff, Djoerd Hiemstra, Michel Ehrenhard

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationConference Proceedings - EMNLP 2015
Subtitle of host publicationConference on Empirical Methods in Natural Language Processing
PublisherAssociation for Computational Linguistics (ACL)
Pages2570-2576
Number of pages7
ISBN (Electronic)9781941643327
Publication statusPublished - 1 Jan 2015
Externally publishedYes
EventConference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Lisbon, Portugal
Duration: 17 Sep 201521 Sep 2015

Publication series

NameConference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing

Conference

ConferenceConference on Empirical Methods in Natural Language Processing, EMNLP 2015
CountryPortugal
CityLisbon
Period17/09/1521/09/15

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