Text-based Sarcasm Detection on Social Networks: A Systematic Review

Sarcasm is a sophisticated phenomenon used for conveying meaning that differs from what being said, and it usually to express displeasure or ridicule others. Sentiment analysis process of uncovering the subjective information text. Detecting figurative language such as irony sarcasm, focused challenging research field sentiment analysis. understanding use sarcasm in social networks could provide businesses politicians with significant insight, since reflects people’s opinions about certain topics, news, products. This has especially become relevant recently because sarcastic texts have been trending on are posted by millions active users. As result this situation, there now an increasing amount detection network posts. Many works published detection, they include wide variety techniques based rules, lexicons, traditional machine learning, deep transformers. However, task due ambiguity non-straightforward nature In addition, very few reviews conducted area. Therefore, systematic review mainly aims at exploring newly articles years between 2019 2022. Several databases were extensively searched, 30 met criteria included. The selected reviewed their approaches, datasets, evaluation metrics. findings emphasized learning most commonly technique recent literature, Twitter F-measure source performance metric, respectively. Finally, article presents brief discussion regarding challenges future directions.