A Chatbot for the Elicitation of Contextual Information from User Feedback

Paper in proceeding, 2022

Over the last years, user feedback has become a valuable source for requirements elicitation. Software vendors increasingly rely on user feedback to collect product issues and feature requests, discover requirements and monitor the overall sentiment of the users about a product. While the analysis of user feedback for requirements elicitation has revealed that feedback can contain helpful information for the product team, collecting valuable, informative, and actionable feedback is still challenging: User feedback is often vague, emotional, or missing important information, such as contextual information, to actually support a product team. Information describing the context of the reported feedback, such as the device model and software version, plays an essential role in increasing its value [1], [2]. Without a given context, reported issues can be complex to understand, reproduce, and address.