Work

Using Hedge Detection to Improve Committed Belief Tagging

Year: 2018

Type: conference-paper

Abstract: We describe a novel method for identifying hedge terms using a set of manually constructed rules.We present experiments adding hedge features to a committed belief system to improve classification.We compare performance of this system (a) without hedging features, (b) with dictionary-based features, and (c) with rule-based features.We find that using hedge features improves performance of the committed belief system, particularly in identifying instances of non-committed belief and reported belief.

DOI: 10.18653/v1/w18-1301

Authors: Morgan Ulinski, Seth Benjamin, Julia Hirschberg

Institution: Columbia University

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funders: U.S. Department of Defense, Defense Advanced Research Projects Agency

OpenAlex ID: W2807597433

FWCI: 0.398

Cites: 8

Cited by: 8

Related to: 10