Advancing Tourism Chatbots: Understanding Irony, Sarcasm, and Negative Emotions of Users
Ommi Balamurali, A.M. Abhishek Sai, Sruthy Anand · 2024
The recent trend in chatbots for several application areas shows their potential to act as a support system to assist users with their needs. However, there is a need to direct efforts to build emotional intelligence into this software to enhance its usability and user experience. Building emotionally intelligent chatbots helps to interpret and respond to users according to their emotions, resulting in rich and healthy user experiences. Understanding irony, sarcasm and Negative emotions of the user are important aspects of sentimental analysis as they largely affect the emotional tone. This research utilises Long Short-Term Memory (LSTM) networks, to enhance chatbot sentiment analysis. In our experimentation, we leverage a dataset comprising over a million comments from Reddit, distinguishing between sarcastic and non-sarcastic expressions, to train and test our LSTM model. Along with the utilization of LSTMs Networks for sentiment analysis in the chatbot, the experiment incorporates BERT, a Transformer model architecture, to further enhance the chatbot’s capacity to recognize and react to sarcasm and satire. Using BERT’s capacity for contextual comprehension and pre-trained languages, the conversational agent can resonate with the user’s input tone and intent, whether they are sarcastic or not.