The impact of sentiment analysis on the user experience of chatbots

Abstract

Chatbots have become more popular over the years, however the use of chatbots does not come without problems. This study looked at if sentiment analysis was able to solve these problems and thus see the impact it had on the user experience. The Technology Acceptance Model (TAM) was used to measure the user experience, because it allows an analysis of the impact of an external factor, in this case sentiment analysis, on the user experience. When a user uses a chatbot they have a certain user experience during the interaction. This makes it relevant to measure the experience to see how much sentiment analysis can improve it. Sentiment analysis was used because it is proven that the combination of a chatbot and sentiment seems relevant in making the conversation between a human and a chatbot more clear, sensical and improve the usability (Almansor et al., 2021). The results presented in this experiment showed that sentiment analysis had no impact on the user experience and thus sentiment analysis did not improve the chatbot usability. This could have been because of the small sample size, representation of chatbot users, or even the repetitive side of the chatbot that performed sentiment analysis, or the main topic of the conversation did not require sentiment analysis to be performed.