Facebook Kullanıcılarının Kişilik, İlgi Alanı ve Yaşam Memnuniyeti Analizi

Öz

Günümüzde, e-ticaret sistemleri tarafından toplanan veriler, müşterilerin geleneksel istatistiksel ve demografik bilgilerinin ötesindedir. Sağlanan yorumlar, beğeniler, etiketler, fotoğraflar vb. sayesinde bir uygulamanın kullanıcıları hakkında daha fazla bilgi sahibi olmak mümkün olmaktadir. Kullanıcı davranışlarını ve özelliklerini analiz etmek amacıyla, bu çalışmada, myPersonality veri setinin kişilik,  Zeka Katsayısı,Yaşam Memnuniyeti Ölçeği puanlarına sahip kullanıcıları içeren 3 altkümesi, kullanıcıların beğendiği  kayıtlar ile birleştirilerek, on iki ilgi kategorisine ayrılımış ve Apriori algoritması kullanarak test edilmiştir. Sonuç olarak, türetilmiş ilişkilendirme kuralları sayesinde, Facebook kullanıcılarının kişisel özellikleri ile ilgi kategorileri arasındaki ilişkiler elde edilmiştir.

Anahtar Kelimeler

• Facebook beğenileri
• İlgi Alanı
• İlişkilendirme Kuralları
• Yaşam Memnuniyeti
• Kişilik Özellikleri

The Relationship among Personality, Interest, and Life Satisfaction of Facebook Users

Abstract

Today, the data collected by e-commerce systems are beyond the traditional statistical and demographic information of customers. The data provided by comments, likes, tags, photos and more in social media, enable marketing researchers to better evaluate the behavior of the users. Therefore to analyze user behavior and characteristics, in this paper, 3 balanced subset of myPersonality Facebook dataset is tested by Apriori algorithm. As a result the relationship among personality traits, intelligence quotient , satisfaction with life scale and the assigned 12 interest categories of users are analyzed. 

Keywords

• Facebook likes
• Interest
• Association Rules
• Life Satisfaction
• Personality Traits

References

1. Agrawal, R., Imielinski, T., Swami, A. (1993, May). Mi-ng associations between sets of items in massive databases. In Proc. 1993 ACM-SIGMOD Int. Conf (pp. 207-216).
2. Alam, F., Stepanov, Evgeny A.; Rıccardı, Giusepp. (2013, June). Personality traits recog-tion on social network-facebook. In Seventh International AAAI Conference on Weblogs and Social Media.
3. Bachrach, Y., Kosinski, M., Graepel, T., Kohli, P., & Stillwell, D. (2012, June). Personality and patterns of Facebook usage. In Proceedings of the 4th annual ACM web science conference (pp. 24-32). ACM.
4. Brin, S., Motwa-, R., Ullman, J. D., & Tsur, S.S. (1997a). Dynamic itemset counting and implication rules for market basket data. Acm Sigmod Record, 26(2), 255-264.
5. Brin, S., Motwa-, R., Ullman, J. D., & Tsur, S.( 1997b) Dynamic itemset counting and implication rules for market basket data. In SIGMOD 1997, Proceedings ACM SIGMOD International Conference on Management of Data, pages 255-264, Tucson, Arizona, USA,
6. Brusilovski, P., Alfred K., and Wolfgang N. (2007). The adaptive web: methods and strategies of web personalization (Vol. 4321). Springer Science & Business Media.
7. Cantador, I. Fernández-Tobías, I., Bellogín, A. (2013). Relating personality types with user preferences in multiple entertainment domains. In CEUR workshop proceedings.
8. Celli, F., Pianesi, F., Stillwell, D., & Kosinski, M. (2013, June). Workshop on computational personality recog-tion: Shared task. In Seventh International AAAI Conference on Weblogs and Social Media.

9. Chawla, N. V., Bowyer, K. W., Hall, L. O., & Kegelmeyer, W. P. (2002). SMOTE: synthetic minority over-sampling tech-que. Journal of artificial intelligence research, 16, 321-357.
10. Costa, P.T., McCrae, Robert. R. (2008). The revised neo personality inventory (neo-pi-r)." The SAGE handbook of personality theory and assessment 2, 2(2), 179-198.
11. Digman, J.M. (1989). Five robust trait dimensions: Development, stability, and utility. Journal of personality, 57(2), 195-214.
12. Farnadi, G., Zoghbi, S., Moens, M. F., & De Cock, M. (2013, June). Recog-sing personality traits using Facebook status updates. In Seventh International AAAI Conference on Weblogs and Social Media.
13. Garner, S. R. (1995, April). Weka: The waikato environment for knowledge analysis. In Proceedings of the New Zealand computer science research students conference (pp. 57-64).
14. Golbeck, J., Robles, C. T. (2011, May). Predicting personality with social media. In CHI'11 extended abstracts on human factors in computing systems (pp. 253-262). ACM.
15. Goldberg, L.R., Johnson, J.A., Eber, H.W., Hogan, R., Ashton, M.C., Clo-nger, C.R., & Gough, H.G. (2006). The international personality item pool and the future of public-domain personality measures. Journal of Research in personality, 40(1), 84-96.
16. HU, R., PU, P. (2011, October). Enhancing collaborative filtering systems with personality information. In Proceedings of the fifth ACM conference on Recommender systems (pp. 197-204). ACM.
17. Kaufman, S.B., Quilty, L. C., Grazioplene, R.G., Hirsh, J. B., Gray, J. R., Peterson, J. B., & DeYoung, C. G. (2016). Openness to experience and intellect differentially predict creative achievement in the arts and sciences. Journal of personality, 84(2), 248-258.
18. Kosinski, M., & Stillwell, D. J. (2011). myPersonality research wiki. myPersonality project. Unpublished manuscript.
19. Markovikj, D., Gievska, S., Kosinski, M., & Stillwell, D. J. (2013, June). Mi-ng facebook data for predictive personality modeling. In Seventh International AAAI Conference on Weblogs and Social Media.
20. Pennebaker, J. W., Francıs, M. E., Booth, R. J. (2001). Linguistic inquiry and word count: LIWC 2001. Mahway: Lawrence Erlbaum Associates, 71(2001)
21. Pennebaker, J.W.; King, L. A. (1999). Linguistic styles: Language use as an individual difference. Journal of personality and social psychology, 77(6), 1296.
22. Piatetsky-Shapiro, G. (1991). Discovery, analysis, and presentation of strong rules. Knowledge discovery in databases, 229-238.
23. Roshchina, A. (2012). TWIN: Personality-based Recommender System. Institute of Technology Tallaght, Dublin.
24. Schacter, D. L., Gilbert, D. T., & Wegner, D. M. (2010). Implicit memory and explicit memory. Psychology, 238.
25. Schimmack, U., Radhakrishnan, P., Oishi, S., Dzokoto, V., & Ahadi, S. (2002). Culture, personality, and subjective well-being: Integrating process models of life satisfaction. Journal of personality and social psychology, 82(4), 582.
26. Schwartz, H. A., Eichstaedt, J. C., Kern, M. L., Dziurzynski, L., Ramones, S. M., Agrawal, M., & Ungar, L. H. (2013). Personality, gender, and age in the language of social media: The open-vocabulary approach. PloS one, 8(9), e73791.
27. Sternberg, R.J., Kaufman, Scott B. (2011). The Cambridge handbook of intelligence. Cambridge U-versity Press.
28. Witten I.H., Frank E.( 2000). Data Mi-ng: Practical Machine Lear-ng Tool and Tech-que with Java Implementation. Morgan Kaufmann; 2000.
29. Yarko-, T. (2010). Personality in 100,000 words: A large-scale analysis of personality and word use among bloggers. Journal of research in personality, 44(3), 363-373.
30. Zhan L., Sun Y., Wang, N., & Zhang, X. (2016). Understanding the influence of social media on people’s life satisfaction through two competing explanatory mecha-sms. Aslib Journal of Information Management, 68(3), 347-361.