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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 4
961-974

Comprehensive review of sarcasm detection for social media

Yu Bengonga,b
Li Chenyuea
a. School of Management, b. Key Laboratory of Process Optimization & Intelligent Decision-Making(Ministry of Education), Hefei University of Technology, Hefei 230009, China
DOI: 10.19734/j.issn.1001-3695.2024.08.0317

Abstract

In recent years, online social media platforms have become saturated with a diverse range of free expression, lea-ding to heightened attention on the detection of sarcastic semantics as a specialized form of sentiment analysis. To enhance the study of sarcasm detection in social media contexts, this paper reviewed the evolution of both traditional methodologies and deep learning techniques, systematically analyzing their developmental trends from two perspectives: textual sarcasm detection and multimodal sarcasm detection. Firstly, this paper compiled and summarized the datasets utilized for sarcasm detection. Next, this paper investigated sentence-level detection, contextual augmentation, knowledge integration, and auxiliary tasks within textual sarcasm detection. This paper elaborated on the contributions of attention mechanisms, pre-trained models, graph neural networks, and quantum neural networks in the fusion of multimodal sarcastic information. Subsequently, this paper explored the potential applications within this domain. Finally, this paper encapsulated the current state of research, identified existing challenges, and proposed potential research directions for sarcasm detection, incorporating recent advancements in large language models to provide valuable guidance for future researchers aiming to innovate detection methodologies.

Foundation Support

国家自然科学基金资助项目(72071061)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.08.0317
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 4
Section: Survey
Pages: 961-974
Serial Number: 1001-3695(2025)04-001-0961-14

Publish History

[2025-04-05] Printed Article

Cite This Article

余本功, 李晨越. 面向社交媒体的讽刺检测研究综述 [J]. 计算机应用研究, 2025, 42 (4): 961-974. (Yu Bengong, Li Chenyue. Comprehensive review of sarcasm detection for social media [J]. Application Research of Computers, 2025, 42 (4): 961-974. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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