Stance-Taking in Topics Extracted from Vaccine-Related Tweets and Discussion Forum Posts

Maria Skeppstedt, Manfred Stede, Andreas Kerren


Abstract
The occurrence of stance-taking towards vaccination was measured in documents extracted by topic modelling from two different corpora, one discussion forum corpus and one tweet corpus. For some of the topics extracted, their most closely associated documents contained a proportion of vaccine stance-taking texts that exceeded the corpus average by a large margin. These extracted document sets would, therefore, form a useful resource in a process for computer-assisted analysis of argumentation on the subject of vaccination.
Anthology ID:
W18-5902
Volume:
Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task
Month:
October
Year:
2018
Address:
Brussels, Belgium
Editors:
Graciela Gonzalez-Hernandez, Davy Weissenbacher, Abeed Sarker, Michael Paul
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5–8
Language:
URL:
https://aclanthology.org/W18-5902
DOI:
10.18653/v1/W18-5902
Bibkey:
Cite (ACL):
Maria Skeppstedt, Manfred Stede, and Andreas Kerren. 2018. Stance-Taking in Topics Extracted from Vaccine-Related Tweets and Discussion Forum Posts. In Proceedings of the 2018 EMNLP Workshop SMM4H: The 3rd Social Media Mining for Health Applications Workshop & Shared Task, pages 5–8, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Stance-Taking in Topics Extracted from Vaccine-Related Tweets and Discussion Forum Posts (Skeppstedt et al., EMNLP 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-5902.pdf