Annotating Claims in the Vaccination Debate

7Citations
Citations of this article
80Readers
Mendeley users who have this article in their library.

Abstract

In this paper we present annotation experiments with three different annotation schemes for the identification of argument components in texts related to the vaccination debate. Identifying claims about vaccinations made by participants in the debate is of great societal interest, as the decision to vaccinate or not has impact in public health and safety. Since most corpora that have been annotated with argumentation information contain texts that belong to a specific genre and have a well defined argumentation structure, we needed to adjust the annotation schemes to our corpus, which contains heterogeneous texts from the Web. We started with a complex annotation scheme that had to be simplified due to low IAA. In our final experiment, which focused on annotating claims, annotators reached 57.3% IAA.

Cite

CITATION STYLE

APA

Torsi, B., & Morante, R. (2018). Annotating Claims in the Vaccination Debate. In EMNLP 2018 - Proceedings of the 5th Workshop on Argument Mining (pp. 47–56). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w18-5207

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free