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An Application of Aspect-Based Sentiment Analysis on Teaching Evaluation

Wen Qu and Zhiyong Zhang
University of Notre Dame, Notre Dame IN 46556, USA
wqu@nd.edu

Abstract. With the rapid development of new techniques, text mining has become explosively popular in the past two decades. Various techniques and methods have been developed to manage and analyze text data to exploit the information underlying the text. Among them, the aspect-based sentiment analysis (ABSA), which is a research field that studies people's opinion, sentiment toward attributions or aspects of individual entities, has attracted researchers in both industry and academia. ABSA first extracts the relevant aspects of a specific entity and then determines the sentiment for each aspect. To our knowledge, there is no ready-to-use R packages or functions for ABSA. In this study, a brief review of ABSA is conducted and applied to a teaching evaluation study. It is also illustrated how to conduct ABSA using R.

Keywords: Aspect-based sentiment analysis • Teaching evaluation • Text data.

DOI: https://doi.org/10.35566/isdsa2019c6


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