Recognizing Sarcasm in Chatbot Response using Python

Nilavani K,Yamini D, Vasunthra R

Department of Information Technology, Agni College of Technology, India

IJTCSE-ISSN 2349–1582

Volume No :10, Issue:02

Accepted for June 2023 Issue

Abstract

Recognizing sarcasm is important in chatbot responses because it can help the bot understand the user’s intent and respond appropriately. By identifying sarcasm, chatbots can avoid misunderstandings and provide more effective and relevant responses, ultimately improving the user experience.chatbots can better understand the intent behind user statements and provide more accurate and engaging responses. This, in turn, can lead to improved user satisfaction and a more positive perception of the chatbot’s abilities.Sarcasm is a form of communication that relies on irony, humor, and context. Recognizing sarcasm in text poses a significant challenge due to its subtle and nuanced nature. While machine learning (ML), deep learning (DL), and natural language processing (NLP) techniques have proven effective in sarcasm detection, this abstract proposes a rule-based approach to identify sarcasm using Python, without employing ML, DL, or NLP. The proposed method leverages linguistic patterns and contextual cues to capture the essence of sarcasm. By utilizing a set of handcrafted rules and predefined indicators, this approach aims to identify sarcastic statements in a straightforward and interpretable manner. It does not require extensive training datasets or complex models, making it accessible to Python developers who may have limited experience with ML or NLP techniques.The system’s implementation involves tokenizing the text into words, and then analyzing the presence of specific linguistic structures such as negations, exaggerations, contradictions, and wordplay. Additionally, the context surrounding a statement is considered, including the speaker’s intent, emotional cues, and potential incongruities between the explicit and implicit meanings.