-3bf97310184a13a8c1e-184 20230225053132320 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 03 30 2023 11 6 Department of Computer Science and Engineering – Artificial Intelligence, Indira Gandhi Delhi Technical University for Women, Kashmere Gate, Delhi, India Spriha Sinha https://orcid.org/0000-0002-6905-1370 Monika Choudhary https://orcid.org/0000-0003-1579-140X Department of Computer Science and Engineering, Indira Gandhi Delhi Technical University for Women, Kashmere Gate, Delhi, India Emotions are something that makes one realize how other people are feeling but sarcasm needs to be understood by putting in some extra effort. Sarcasm, a verbal irony, is a practice of using words or sentences that are different from their literal meaning. Researchers are still making effort in developing an algorithm that can identify sarcasm completely. Since sometimes humans also take time to understand sarcasm, making a machine learn to recognize is also not a simple task. The need for Deep Learning (DL) is rapidly growing for detection and classification operations. Different research works focused on Sarcasm detection using various methodologies but the issue with existing research work is their performance and accuracy. Our survey provides several helpful examples, the most notable of which is a table that lists prior studies according to several criteria, including the kinds of methodologies with accuracy, and datasets employed. This paper also throws light on multimodal detection, sarcasm detection from typographic images (memes), feature set analysis, and different phases of a model with various issues and milestones in sarcasm detection. 03 30 2023 50 58 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true No, I did not receive. No conflicts of interest to the best of our knowledge. No, the article does not require ethical approval and consent to participate with evidence. Not relevant. Spriha Sinha wrote this paper under the guidance of her supervisor. She collected and analyzed data from various relevant related papers, and made the base of the paper with the help of knowledge gained by reading and analyzing papers with their limitations and future scope. With the help of her supervisor's valuable feedback, guidance, and support throughout the process, she was able to improve the structure of the paper, maintain the standard and ensure the accuracy and validity of the findings. Monika Choudhary She is a great supervisor, who provided valuable guidance and support throughout the research process for this paper. She offered valuable insights on the topic and helped to refine the research methodology. Her feedback and suggestions greatly improved the quality of the paper. 10.35940/ijrte.F7476.0311623 https://www.ijrte.org/portfolio-item/F74760311623/