Opinion Corpus for Assessment of Study Abroad Program

  • Katsunori Kotani Kansai Gaidai University
  • Takehiko Yoshimi Ryukoku University
  • Mayumi Uchida Kansai Gaidai University
Keywords: opinion corpus, study-abroad program assesment, classification, opinion mining, degree of positiveness/happiness

Abstract

This study compiled an opinion corpus for developing a method for automatically evaluating a study-abroad program. Evaluation should cover not only academic experience at a host institution but also intercultural experience in the dormitory and interpersonal experience with local students, which helps improve a study-abroad program. The corpus included 600 students’ opinions on the satisfaction with academic, intercultural and interpersonal experiences, consisting of 40,024 words in total. Each opinion was annotated according to the opinion polarity determined by an existing sentiment classifier automatically. When automatically classified opinion polarity was compared with manually determined opinion polarity, a different distribution was observed. Because the existing classifier was not trained with a corpus that dealt with the issues related to students’ opinions about a study-abroad program, this result suggested the need of a corpus for study-abroad program evaluation. The opinion classifier of this study trained with the opinion corpus demonstrated a higher accuracy (83.5 percent) than the majority class baseline (70.9 percent).

References

El-Halees, Alaa. 2011. Mining opinions in user-generated contents to improve course evaluation. In Jasni Mohamad Zain, Wan Maseri Wan Mohd and Eyas El-Qawasmeh eds. Software engineering and computer systems. Part II, Communications in computer and information science. Berlin: Springer-Verlag Berlin Heidelberg, 107–115.

Engle, Lilli and John Engle. 2004. Assessing language acquisition and intercultural sensitivity development in relation to study abroad program design. Frontiers: The Interdisciplinary Journal of Study Abroad 10: 219–236.

Kaewyong, Phuripoj, Anupong Sukprasert, Naomie Salim and Fatin Aliah Phang. 2015. The possibility of students’ comments automatic interpret using lexicon based sentiment analysis to teacher evaluation. In Proceeding of the 3rd International Conference on Artificial Intelligence and Computer Science, 179–189.

Leong, Chee Kian, Yew Haur Lee and Wai KeongMak. 2012. Mining sentiments in SMS texts for teaching evaluation. Expert Systems with Applications 39: 2584–2589.

Meyer, David. 2012. Support Vector Machines. The interface to libsvm in package e1071. https://datajobs.com/data-science-repo/SVM-in-R-[David-Meyer].pdf (accessed 27 July 2018)

Östmar, Mattias. 2011. Mood. https://www.uclassify.com/browse/prfekt/mood (accessed 27 July 2018)

Savicki, Victor and Elizabeth Brewer eds. 2015. Assessing study abroad: theory, tools, and practice. Sterling, VI: Stylus.

uClassify. 2015. The sentiment classifier. https://www.uclassify.com/browse/uclassify/sentiment (accessed 27 July 2018)

Published
2018-12-31
How to Cite
Kotani, K., Yoshimi, T., & Uchida, M. (2018). Opinion Corpus for Assessment of Study Abroad Program. Research in Corpus Linguistics, 6, 9-13. https://doi.org/10.32714/ricl.06.02
Section
Articles