Work

Sarcasm Target Identification: Dataset and An Introductory Approach

Year: 2018

Type: conference-paper

Abstract: Past work in computational sarcasm deals primarily with sarcasm detection.In this paper, we introduce a novel, related problem: sarcasm target identification (i.e., extracting the target of ridicule in a sarcastic sentence).As a benchmark, we introduce a new dataset for the task.This dataset is manually annotated for the sarcasm target in book snippets and tweets based on our formulation of the task.We then introduce an automatic approach for sarcasm target identification.It is based on a combination of two types of extractors: one based on rules, and another consisting of a statistical classifier.Our introductory approach establishes the viability of sarcasm target identification, and will serve as a baseline for future work.

Source: Language Resources and Evaluation Conference (LREC)

DOI: 10.63317/2xck5kccxygt

Authors: Aditya Joshi, Pranav Goel, Pushpak Bhattacharyya, Mark Carman

Institutions: Indian Institute of Technology Bombay, Indian Institute of Technology BHU, Carnegie Mellon University, Indian Institute of Technology Patna, Monash University

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W2806572670

FWCI: 0.61

Cites: 21

Cited by: 11

Related to: 20