Analyzing Emotional Responses in Human vs Chatbot Interactions using Parrot Theory - Dewi, Erlinda Yunita; Susiati, S (Proceeding ISETH (International Summit on Science, Technology, and Humanity), 2023)
The integration of AI and natural language processing technologies has led to the development of chatbots, which offer sophisticated conversational experiences with users. The effectiveness of chatbots in providing emotional support and empathy to users is a topic of debate, with some studies suggesting that chatbots can provide emotional support to users, while others have indicated that chatbots may lack the ability to understand and respond appropriately to human emotions. This study aims to analyze emotional responses in human vs chatbot interactions using Parrot Theory, which classifies emotions into three groups or levels named as primary, secondary, and tertiary. The data collection process consists of two stages: a literature review and a dataset of human responses and chatbot responses to queries that the researcher has made. The dataset of human responses from 35 participants aged 18-34, with a distribution of 35%, 18-20; 65.7%, 21-29; and 2.9%, 30-34. The gender distribution comprises 25.7% male and 74.3% female respondents. The data analysis involves content analysis and comparison of human and chatbot responses. By annotating the collected data with emotional labels based on Parrot Theory, researchers can identify patterns and differences in emotional expressions between humans and chatbots. The findings indicate that chatbots and humans produce different types of emotions in responding to situations, with human responses often including personal touches, cultural references, and varied language complexity, while chatbot responses are more structured and formal. The reasons for these differences include the level of personalization, cultural references, language complexity, and the ability to express emotions.