| 58725 |
Creator |
8eb9378b0e3dcd225dfc47fcdc9b35f4 |
| 58725 |
Creator |
ext-54ec617f3b6960bd6db1a90cfdea82d9 |
| 58725 |
Creator |
ext-850764054b562c939fd70e82d00298d1 |
| 58725 |
Date |
2016 |
| 58725 |
Is Part Of |
repository |
| 58725 |
abstract |
This paper describes and evaluates a novel feature set for stance classification of
argumentative texts; i.e. deciding whether a post by a user is for or against the
issue being debated. We model the debate both as attitude bearing features, including
a set of automatically acquired ‘topic terms’ associated with a Distributional Lexical
Model (DLM) that captures the writer’s attitude towards the topic term, and as dependency
features that represent the points being made in the debate. The stance of the text
towards the issue being debated is then learnt in a supervised framework as a function
of these features. The main advantage of our feature set is that it is scrutable:
The reasons for a classification can be explained to a human user in natural language.
We also report that our method outperforms previous approaches to stance classification
as well as a range of baselines based on sentiment analysis and topic-sentiment analysis. |
| 58725 |
authorList |
authors |
| 58725 |
presentedAt |
ext-d7be21f84c589b571cf7516a51cc9748 |
| 58725 |
status |
peerReviewed |
| 58725 |
type |
AcademicArticle |
| 58725 |
type |
Article |
| 58725 |
label |
Mandya, Angrosh; Siddharthan, Advaith and Wyner, Adam (2016). Scrutable Feature
Sets for Stance Classification. In: Proceedings of the 3rd Workshop on Argument
Mining, pp. 60–69. |
| 58725 |
label |
Mandya, Angrosh; Siddharthan, Advaith and Wyner, Adam (2016). Scrutable Feature
Sets for Stance Classification. In: Proceedings of the 3rd Workshop on Argument
Mining, pp. 60–69. |
| 58725 |
Title |
Scrutable Feature Sets for Stance Classification |
| 58725 |
in dataset |
oro |