Aspect-based Sentiment Analysis for University Teaching Analytics

Tim Schurig, Sine Zambach, Raghava Rao Mukkamala, Malte Petry

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review


Aspect-based sentiment analysis (ABSA) is a natural language processing method to analyze sentiments from large amounts of unstructured text in a much more fine-grained manner at the aspect level. In this research work, we apply it to analyze open text replies from surveys regarding online teaching. Like most other educational institutions, Copenhagen Business School (CBS) had to shift to online teaching from one day to the next. Using ABSA, we investigated the impact of this forced online learning experiment on teaching quality in the spring semester of 2020. Our findings reveal that students disliked online teaching due to insufficient information and unadjusted teaching methods. However, students liked its flexibility and possibility to learn at an individual pace. We show that ABSA can extract valuable information in an easily interpretable manner to support teaching and learning processes. Finally, our findings show that ABSA is a valuable tool to analyze unstructured text quantitatively.
TitelProceedings of the 30th European Conference on Information Systems (ECIS)
Antal sider18
UdgivelsesstedAtlanta, GA
ForlagAssociation for Information Systems. AIS Electronic Library (AISeL)
StatusUdgivet - 2022
BegivenhedThe 30th European Conference on Information Systems (ECIS) 2022: New Horizons in Digitally United Societies - Universitatea de Vest din Timișoara (UVT) / West University of Timişoara (WUT), Timisoara, Rumænien
Varighed: 19 jun. 202224 jun. 2022
Konferencens nummer: 30


KonferenceThe 30th European Conference on Information Systems (ECIS) 2022
LokationUniversitatea de Vest din Timișoara (UVT) / West University of Timişoara (WUT)
NavnProceedings of the European Conference on Information Systems


  • Aspect-based sentiment analysis
  • Natural language processing
  • Covid-19
  • Open text surverys
  • Online teaching