mlsanityData to 7 Oct 2026

A Survey on Automated Sarcasm Detection on Twitter

arXiv 2202.02516 ↗First posted 5 Feb 2022cs.CLcited by 3

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Abstract (arXiv)

Automatic sarcasm detection is a growing field in computer science. Short text messages are increasingly used for communication, especially over social media platforms such as Twitter. Due to insufficient or missing context, unidentified sarcasm in these messages can invert the meaning of a statement, leading to confusion and communication failures. This paper covers a variety of current methods used for sarcasm detection, including detection by context, posting history and machine learning models. Additionally, a shift towards deep learning methods is observable, likely due to the benefit of using a model with induced instead of discrete features combined with the innovation of transformers.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 46 of its 178 references that are in the map. First posted on arXiv 5 Feb 2022.

Builds on

46 of 178 references.

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Cited by year

Citing papers per year: 2022: 1; 2023: 0; 2024: 2.

3 papers.

  1. 2022BanglaSarc: A Dataset for Sarcasm Detectioncited by 3
  2. 2024KoCoSa: Korean Context-aware Sarcasm Detection Datasetcited by 2
  3. 2024Sarcasm Detection in a Less-Resourced Languagecited by 0