The impact of sentiment analysis on the user experience of chatbots
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2021-06-18
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en
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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.
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Faculteit der Sociale Wetenschappen