E. Kahya Ozyirmidokuz, Assistant Professor, PhD Erciyes University, Turkey, E. A. Stoica, Lecturer, PhD “Lucian Blaga” University, Sibiu, Romania EMOTION BASED ANALYSIS OF TURKISH CUSTOMER OPINIONS

Firms should manage their customer feedback so they can adapt to rapid changes in the environment. They have to interact with their customers to understand them and to turn their opinions into useful knowledge. Understanding customers’ feelings about a product gives firmS competitive advantage through continuous market monitoring. They can thus generate improving strategies about the system to change perceptions that drive the behaviours of the customers. Firms can view their customers’ happiness as a key tool for decision-making. This study calculates online product happiness by using the average emotional valence values of customer opinions. We analyse Turkish opinions about a product over a period of 3 months. We find the averages of the online emotional valence values of the product per month. We also determined the increase in happiness over time. According to the opinion valence values, we found the relations between the documents.

Keywords: opinion mining, emotional analysis, happiness, natural language processing, text mining.

Date of submission 15.05.16

DOI: https://doi.org/10.17721/1728-2667.2016/189-12/6

References

  1. Abdel-Khalek, A. M., (2004) Happiness among Kuwaiti College Students. Journal of Happiness Studies, 5(1), p. 93­97. https://doi.org/10.1023/b:johs.0000021715.45981.40
  2. Bradley, M.M., Lang, P.J., (1999) Affective Norms for English Words (ANEW): Instruction Manual and Affective Ratings, Technical Report C-1, The Center for Research in Psychophysiology, University of Florida, Available at http://www.uvm.edu/~pdodds/teaching/courses/2009-08UVM-300/docs/others/everything/bradley1999a.pdf .
  3. Brew, A., Greene, D., Archambault, D., Cunningham, P., (2011) Deriving Insights from National Happiness Indices, In: 2011 IEEE 11th International Conference on Data Mining Workshops (ICDMW), IEEE International Conference on Data Mining series (ICDM’11), 11-14 December 2011, Vancouver, Canada, p.11-12. https://doi.org/10.1109/icdmw.2011.61
  4. Camillo, F.M., Tosi, M., Traldi, T., (2005) Semiometric Approach, Qualitative Research and Text Mining Techniques for Modelling the Material Culture of Happiness, Studies in Fuzziness and Soft Computing, Ed. by S. Sirmakessis, 185, Berlin: Springer, p. 79-92.
  5. Diener, E., Emmons, R.A., Larsen, R.J., Griffin, S., (1985) The Satisfaction with Life Scale, Journal of Personality Assessment, 49(1), p. 71-75.
  6. Dodds, P.S. and Danforth, C.M., (2010) Measuring the Happiness of Large-scale Written Expression: Songs, Blogs, and Presidents, J Happiness Stud, 11, p. 441-456. https://doi.org/10.1007/s10902-009-9150-9
  7. Dodds, P.S., Clark, E.M., Desu, S., Frank, M.R., Reagan, A.J. et al., (2015) Human Language Reveals a Universal Positivity Bias, PNAS Proceedings of the National Academy of Sciences of the USA, 112, p. 2389-2394.
  8. Fox, E., (2008) Emotion science. Basingstoke, England: Palgrave, Macmillian.
  9. Frey, B.S., Stutzer, A., (2001) Happiness and Economics: How the Economy and Institutions Affect Human Well­being, USA: Princeton University Press.
  10. Hills, P., Argyle, M., (2002) The Oxford Happiness Questionnaire: A Compact Scale for the Measurement of Psychological Well-being, Personality and Individual Differences, 33, p.1073-1082.
  11. Jalloh, A., Flack, T., Chen, K., Fleming, K., (2014) Measuring Happiness: Examining Definitions and Instruments, Illuminare: A Student Journal in Recreation, Parks, and Leisure Studies 12(1), p. 59-67.
  12. Kahneman, D., Krueger, A.B., Schkade, D.A., Schwarz, N., Stone, A.A., (2004) A Survey Method for Characterizing Daily Life Experience: The Day Reconstruction Method, Science, 306(5702), p. 1776-1780.
  13. Kamvar, S.D., Harris, J., (2010) We feel fine and searching the emotional web”, In: Proceedings of the WSDM’11, February 9-12, 2011, ACM 978-1-4503-0493-1/11/02, Hong Kong: China.
  14. Kenny, C., (2015) Pozitif Dü§ünmenin Ekonomik Gücü, Bloomberg Businessweek Türkiye, 18-24 (1), p. 20-21.
  15. Lyubomirsky, S., Lepper, S., (1999) A Measure of Subjective Happiness: Preliminary Reliability and Construct Validation. Social Indicators Research, 46, p.137-155.
  16. Manning, C.D., Raghavan, P., Schütze, , (2008) Introduction to Information Retrieval, Cambridge University Press. Available at http://www-nlp.stanford.edu/IR-book/ .
  17. Mogilner, C., Kamvar, S.D., Aaker, J., (2011) The Shifting Meaning of Happiness, Social Psychological and Personality Science, p.1-8.
  18. Mostafa, M.M., (2013) More than words: Social networks’ TM for Customer Brand Sentiments, Expert System with Applications, 40, p.4241-4251. https://doi.org/10.10167j.eswa.2013.01.019
  19. Neugarten, L., Havinghurst, R.J., Tobin, S.S., (1961) The Measurement of Life Satisfaction, Journal of Gerontology, 16, p.134-143.
  20. Pitic, A., Bucur, C., Stoica, E.A., (2013) Automatic Classification of Messages in Social Media, Case Study for Romanian Language, In: Proceedings of the 1st International Conference for Doctoral Students, IPC 2013, Sibiu, Romania, p.760-769.
  21. Stoica, E.A., Kahya Özyirmidokuz, , (2015) Mining Customer Feedback Documents, International Journal of Knowledge Engineering, 1(1), p.68-71. https://doi.org/10.7763/ijke.2015.v1.12
  22. Stoica, E.A., Pitic A.G, Calin B., (2014) New Media E-marketing Campaign. Case Study for a Romanian Press Trust, Procedia Economics and Finance, 16, p. 635 -640. https://doi.org/10.1016/s2212-5671(14)00851-x
  23. Stoica, E.A., Pitic, A., Mihaescu, L., (2013) A Novel Model for E-Business and E-Government Processes on Social Media, In: Proceedings of the International Economic Conference of Sibiu 2013 Post Crisis Economy: Challenges and Opportunities, IECS 2013, Procedia Economics and Finance, 6, p.760- 769.
  24. Surowiecki, J., (2005) The Wisdom of Crowds. Random House LLC.
  25. Thelwall, M., Buckley, K., Paltoglou, G., (2011) Sentiment in Twitter Events, Journal of the Americal Society for Information Science and Technology, 62(2), p. 406-418.
  26. Ura, K., Alkire, S., Zangmo, T., Wangdi, K., (2012) A Short Guide to Gross National Happiness Index, The Centre for Bhutan Studies, Available at http://www.grossnationalhappiness.com/wp-content/uploads/2012/04/Short-GNH-Index- edited.pdf.
  27. Veenhoven, R, (2012a) World database of happiness: Continuous register of scientific research on subjective appreciation of life. Netherlands: Erasmus University Rotterdam.
  28. Veenhoven, , (1984) Conditions of Happiness. Dordrecht, Netherlands: Kluwer (now Springer).
  29. Veenhoven, , (2012b) Bibliography of Happiness. (Section F ‘Happiness and Society’), World database of happiness, Netherlands: Erasmus University Rotterdam.
  30. Yassine, M., Hajj, H., (2010) A Framework for Emotion Mining from Text in Online Social Networks, In: 2010 IEEE International Conference on Data Mining Workshops, p. 1136-1142.
  31. You, S., DesArmo, J., Joo, S., (2013) Measuring Happiness of US Cities by Mining User-generated Text in Flickr.com: A Pilot Analysis, In: Proceedings of the American Society for Information Science and Technology, November 1­6, 2013, Montreal, Quebec, Canada, 50(1), p.1-4. https://doi.org/10.1002/meet.14505001167

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