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Free-text comments provided by Respondents in the Service Effectiveness Assessment offer rich insight into staff members' experiences of their university's support services. Nous Data Insights has developed emotion-based sentiment classifications using natural language processing (NLP) techniques to help your university extract insight from these comments more quickly.
Sentiment classifications help service owners & faculty managers to quickly identify the aspects of a service that have led staff members to express frustration, disappointment, confusion, and a range of other emotions. Some questions that service owners & faculty managers may want to answer using sentiment classifications include:
- What are the most common sentiments for a service or function?
- What issues do confused, disappointed, or annoyed Respondents raise?
- What leads service users to express admiration and approval?
Interested in analysing your Service Effectiveness results using sentiment classifications?
Free trial access to sentiment classifications for service-level and overall free text comments is available now in the Service Effectiveness Application in UFAnalytics
