Research Area:  Machine Learning

Abstract:

Identification of argumentative components is an important stage of argument mining. Lexicon information is reported as one of the most frequently used features in the argument mining research. In this paper, we propose a methodology to integrate lexicon information into a neural network model by attention mechanism. We conduct experiments on the UKP dataset, which is collected from heterogeneous sources and contains several text types, e.g., microblog, Wikipedia, and news. We explore lexicons from various application scenarios such as sentiment analysis and emotion detection. We also compare the experimental results of leveraging different lexicons.

Keywords:  

Author(s) Name:  Jian-Fu Lin, Kuo Yu Huang, Hen-Hsen Huang, Hsin-Hsi Chen

Publisher name:  ACL

DOI:  10.18653/v1/W19-4508

Volume Information:  

Paper Link:   https://aclanthology.org/W19-4508/