Log In Sign Up

Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms

by   Patrick Lee, et al.

This paper presents a linguistically driven proof of concept for finding potentially euphemistic terms, or PETs. Acknowledging that PETs tend to be commonly used expressions for a certain range of sensitive topics, we make use of distributional similarities to select and filter phrase candidates from a sentence and rank them using a set of simple sentiment-based metrics. We present the results of our approach tested on a corpus of sentences containing euphemisms, demonstrating its efficacy for detecting single and multi-word PETs from a broad range of topics. We also discuss future potential for sentiment-based methods on this task.


page 1

page 2

page 3

page 4


Extractive and Abstractive Sentence Labelling of Sentiment-bearing Topics

This paper tackles the problem of automatically labelling sentiment-bear...

Semi-Supervised Affective Meaning Lexicon Expansion Using Semantic and Distributed Word Representations

In this paper, we propose an extension to graph-based sentiment lexicon ...

A Report on the Euphemisms Detection Shared Task

This paper presents The Shared Task on Euphemism Detection for the Third...

LiSSS: A toy corpus of Literary Spanish Sentences Sentiment for Emotions Detection

In this work we present a new and small corpus in the area of Computatio...

CATs are Fuzzy PETs: A Corpus and Analysis of Potentially Euphemistic Terms

Euphemisms have not received much attention in natural language processi...

Improving Hypernymy Detection with an Integrated Path-based and Distributional Method

Detecting hypernymy relations is a key task in NLP, which is addressed i...

Discourse Behavior of Older Adults Interacting With a Dialogue Agent Competent in Multiple Topics

We present some results concerning the dialogue behavior and inferred se...