The Study of User Experience Interview Using Semantic Analysis and Short-Term Memory Chatbot

There are many ways to study user experience, each with its own strengths and weaknesses. One popular method is questionnaires. However, questionnaires may not provide deep insights. Phanupong’s research proposed a chatbot using semantic analysis and short-term memory called SEBASS. This chatbot uses a customized semantic short-term memory with RDF as a knowledge representative for the chatbot’s memory. We applied SEBASS, a semantic short-term memory service chatbot, to query the user experience of the MICROSOFT® TEAMS application. Comparison with traditional chatbot and online interview, results show that both BASELINE chatbot and traditional chatbot can effectively interact with the participants in querying the user experience of the MICROSOFT® TEAMS application. Compared to online interviews conducted by humans, the SEBASS chatbot is equally effective in extracting insight user interface information as evidenced by high average scores in specificity, clarity, average number of nodes, and percentage of depth in UI knowledge RDF.