research-article

Irony Detection in Twitter: The Role of Affective Content

Authors:

Delia Irazú Hernańdez Farías,

Paolo RossoAuthors Info & Claims

ACM Transactions on Internet Technology (TOIT), Volume 16, Issue 3

Article No.: 19, Pages 1 - 24

https://doi.org/10.1145/2930663

Published: 09 July 2016 Publication History

Abstract

Irony has been proven to be pervasive in social media, posing a challenge to sentiment analysis systems. It is a creative linguistic phenomenon where affect-related aspects play a key role. In this work, we address the problem of detecting irony in tweets, casting it as a classification problem. We propose a novel model that explores the use of affective features based on a wide range of lexical resources available for English, reflecting different facets of affect. Classification experiments over different corpora show that affective information helps in distinguishing among ironic and nonironic tweets. Our model outperforms the state of the art in almost all cases.

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Cited By

Song LZhao ZMa YLiu YLi J(2024)Utterance-Level Incongruity Learning Network for Multimodal Sarcasm Detection2024 26th International Conference on Advanced Communications Technology (ICACT)10.23919/ICACT60172.2024.10472003(43-49)Online publication date: 4-Feb-2024
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Index Terms

Irony Detection in Twitter: The Role of Affective Content
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Social media

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cover image ACM Transactions on Internet Technology

ACM Transactions on Internet Technology Volume 16, Issue 3

August 2016

156 pages

ISSN:1533-5399

EISSN:1557-6051

DOI:10.1145/2926746

Editor:
Munindar P. Singh
Department of Computer Science, North Carolina State University

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Copyright © 2016 ACM.

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Publication History

Published: 09 July 2016

Accepted: 01 April 2016

Revised: 01 March 2016

Received: 01 December 2015

Published in TOIT Volume 16, Issue 3

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Delia Irazú Hernández Farías
Generalitat Valenciana
Universitat Politècnica de València within the framework of a fellowship of the University of Turin cofunded by Fondazione CRT (World Wide Style Program 2)
SomEMBED TIN2015-71147-C2-1-P MINECO research project

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https://doi.org/10.23919/ICACT60172.2024.10472003
Zhou LXu XWang X(2024)BNS-Net: A Dual-Channel Sarcasm Detection Method Considering Behavior-Level and Sentence-Level Conflicts2024 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN60899.2024.10651549(1-9)Online publication date: 30-Jun-2024
https://doi.org/10.1109/IJCNN60899.2024.10651549
Balamurali OAbhishek Sai AAnand S(2024)Advancing Tourism Chatbots: Understanding Irony, Sarcasm, and Negative Emotions of Users2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT61001.2024.10723883(1-7)Online publication date: 24-Jun-2024
https://doi.org/10.1109/ICCCNT61001.2024.10723883
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