Introducing Sentiment Analysis for the Evaluation of Library’s Services Effectiveness

Abstract

Increasingly, text mining approaches have come to academic and commercial foreground as an effective solution for managing textual resources. Users‟ and consumers‟ comments and reviews hyper proliferation due to web 2.0 emergence, generated the need for such techniques implementation as a way to get insights from an active world expressed textually and not limited to specific scales and options. Sentiment analysis constitutes a NLP method aiming at sentiment detection out of textual snippets. On the other hand, it is a common truth that academic libraries have been intensively based their evaluation attempts on quantitative methods. The current study proposes the use of Sentiment analysis on user comments about Hellenic Open University Distance Library and Information Center which were included to the institutional annual survey. The analysis highlighted latent information about specific aspects of the library that couldn‟t be detected through the constraints that scaling pοses.