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2017 | 17 | nr 1 | 52--60
Tytuł artykułu

Sentiment Discovery and Analysis as a Mean of Student Experience Improvement

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Sentiment analysis has found broad usage helping institutions to better understand the choices, intentions, and behaviors of an individual acting as a buyer, consumer or service user. However its utilization in the domain of higher education is scarce. Therefore, the paper provides an insight into most relevant research and diversified applications of sentiment analysis in higher education, describing its unexploited potentials and benefits, such as leveraging students' attraction/retention, evaluating the institution's competitiveness or tracking performance indicators over time. (original abstract)
Rocznik
Tom
17
Numer
Strony
52--60
Opis fizyczny
Twórcy
  • University of Novi Sad, Republic of Serbia
  • University of Novi Sad, Republic of Serbia
Bibliografia
  • Altrabsheh, N., Cocea, M., & Fallahkhair, S. (2014). Learning Sentiment from Students' Feedback for Real-Time Interventions in Classrooms. Adaptive and Intelligent Systems. 8779. 40-49. Springer International Publishing.
  • Altrabsheh, N., Gaber, M.M., & Cocea, M. (2013). SA-E: sentiment analysis for education. Proceedings of the 5th KES International Conference on Intelligent Decision Technologies, Sesimbra, Portugal. Vol. 255.
  • Dave, K., Lawrence, S., & Pennock, D.M. (2003). Mining the Peanut Gallery: Opinion Extraction and Semantic Classification of Product Reviews. Proceedings of the 12th international conference on World Wide Web. ACM New York, NY, USA.
  • Feldman, R., Rosenfeld, B., Bar-Haim, R., & Fresko, M. (2011). The Stock Sonar - Sentiment Analysis of Stocks Based on a Hybrid Approach. Proceedings of the 23rd IAAI Conference on Artificial Intelligence, San Francisco, USA.
  • Grafsgaard, J.F., Wiggins, J.B., Boyer, K.E., Wiebe, E.N., & Lester, J.C. (2013). Embodied Affect in Tutorial Dialogue: Student Gesture and Posture. Proceedings of the 16th International Conference on Artificial Intelligence in Education, Memphis, United States. Springer-Verlag Berlin Heidelberg.
  • Grljević, O. (2016). Sentiment in the content of social networks as an instrument for improving the operations of higher education institutions (Sentiment u sadržajima društvenih mreža kao instrument unapređenja poslovanja visokoškolskih institucija). University of Novi Sad.
  • Hosterman, A.R. (2013). Tweeting 101: Twitter and the College Classroom. In H.S. Noor Al-Deen, & J.A. Hendricks, Social media usage and impact (pp. 93-111). Lexington Books.
  • Hovy, E., & Lavid, J. (2010). Towards a 'Science' of Corpus Annotation: A New Methodological Challenge for Corpus Linguistics. International Journal of Translation, 22(1), 13-36.
  • Kim, J., Shaw, E., Wyner, S., Kim, T., & Li, J. (2010). Discerning Affect in Student Discussions. Proceedings of the Annual Meeting of the Cognitive Science Society, Portland, Oregon.
  • Lewis, B.K., & Nichols, C. (2013). Attitudes and Perceptions about Social Media Among College Students and Professionals Involved and Not Involved in Strategic Communications. In H.S. Noor Al-Deen, & J.A. Hendricks, Social media usage and impact (pp. 129-145). Lexington Books.
  • Litman, D.J., & Forbes-Riley, K. (2004). Annotating Student Emotional States in Spoken Tutoring Dialogues. Proceedings of the 5th SIGdial Workshop on Discourse and Dialogue, Boston, USA.
  • Liu, B. (2012). Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers.
  • Marques, A.M., Krejci, R., Siqueira, S.W.M., Pimentel, M., & Braz, M.H.L.B. (2013). Structuring the discourse on social networks for learning: Case studies on blogs and microblogs. Computers in Human Behavior, 29(2), 395-400.
  • McGlohon, M., Glance, N., & Reiter, Z. (2010). Star Quality: Aggregating Reviews to Rank Products and Merchants. Proceedings of the 4th International AAAI Conference on Weblogs and Social Media, Washington, DC, USA.
  • Medhat, W., Hassan, A., & Korashy, H. (2014). Sentiment analysis algorithms and applications: A survey. Ain Shams Engineering Journal, 5, 1093-1113.
  • Nasukawa, T., & Yi, J. (2003). Sentiment analysis: capturing favorability using natural language processing. Proceedings of the 2nd international conference on Knowledge capture, Sanibel Island, FL, USA.
  • Nielsen, R.D., Ward, W., Martin, J., & Palmer, M. (2008). Annotating Students' Understanding of Science Concepts. Proceedings of the 6th International Conference on Language Resources and Evaluation, Marrakech, Marocco.
  • Read, J. (2005). Using emoticons to reduce dependency in machine learning techniques for sentiment classification. ACL Student Research Workshop, Ann Arbor, Michigan, USA.
  • Wen, M., Yang, D., & Rose C. (2014). Sentiment Analysis in MOOC Discussion Forums: What does it tell us? Proceedings of the 7th International Conference on Educational Data Mining, London, UK.
  • Wissler, L., Almashraee, M., Monett, D., & Paschke, A. (2014). The Gold Standard in Corpus Annotation. Proceedings of the 5th IEEE Germany Student Conference, IEEE GSC 2014. Passau, Germany.
  • Wyner, S., Shaw, E., Kim, T., Li, J., & Kim, J. (2009). Sentiment Analysis of a Student Q&A Board for Computer Science. Proceedings of the IJCAI workshop on Computational Models of Natural Argument, Pasadena, CA.
  • Yaros, R.A. (2013). Social Media in Education: Effects of Personalization and Interactivity on Engagement and Collaboration. In H.S. Noor Al-Deen, & J.A. Hendricks, Social media usage and impact (pp. 57-75). Lexington Books.
  • Yi, J., Nasukawa, T., Bunescu, R., & Niblack, W. (2003). Sentiment Analyzer: Extracting sentiments about a given topic using natural language processing technique. IEEE International Conference on Data Mining ICDM, Melbourne, FL, USA.
  • Yoo, J., & Kim, J. (2014). Capturing Difficulty Expressions in Student Online Q&A Discussions. Proceedings of the 28th {AAAI} Conference on Artificial Intelligence, Québec City, Québec, Canada.
  • Zeng, L., Hall, H., & Jackson Pitts, M. (2013). Cultivating a Community of Learners: The Potential Challenges of Social Media in Higher Education. In H.S. Noor Al-Deen, & J.A. Hendricks, Social media usage and impact (pp. 111-129). Lexington Books.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171501228

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