A Human-Computer Negotiation Model Based on Sentiment Analysis and Big Data

This paper presents an adaptive negotiation model for AI-powered customer service chatbots in e-commerce. While current chatbots handle basic inquiries, they need advanced negotiation capabilities that consider users’ needs and emotional states, leading to subpar experiences. The proposed model uses big data analytics and sentiment analysis to create personalised negotiation strategies, addressing emotions like anger, joy, and fear. Extensive experiments show that the model effectively manages negative emotions through contextual bargaining, maximising mutual gains for users and businesses. The result is an AI chatbot with enhanced negotiation capabilities, leading to higher customer satisfaction by achieving user-accepted agreements. This research highlights the potential of integrating big data, sentiment analysis, and psychological principles in AI to develop next-generation conversational agents that negotiate like humans, significantly improving customer service and engagement in e-commerce.