Skip to main content
SpringerLink
Log in

Big5 Tool for Tracking Personality Traits

  • Conference paper
  • First Online:
Intelligent Information and Database Systems (ACIIDS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11431))

Included in the following conference series:

Abstract

In the big data era, understanding consumers through digital data is as important as the approach and exploitation of customers through their behavioral and personality traits in the digital world. First, a data warehouse has been studied and developed to extract, transform and load big mobile log data. Afterwards, the data warehouse’s data cubes are aggregated and used to calculate a set of Big5 indicators. Hereafter, Big5 traits can be predicted based on those just-specified indicators. To proof of our concepts, implementation results will be presented in the context of the Big5 tool, which has been designed and developed to predict Big5 personalities in a representative manner.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Alam, F., Stepanov, E.A., Riccardi, G.: Personality traits recognition on social network-facebook. In: Proceedings of Workshop on Computational Personality Recognition, pp. 6–9. AAAI Press, Melon Park (2013)

    Google Scholar 

  2. CNN: Your phone company is selling your personal data. http://money.cnn.com/2011/11/01/technology/verizonattsprinttmobileprivacy/index.htm

  3. de Montjoye, Y.A., Quoidbach, J., Robic, F., Pentland, A.: Predicting personality using novel mobile phone-based metrics. In: Greenberg, A.M., Kennedy, W.G., Bos, N.D. (eds.) Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013. Lecture Notes in Computer Science, vol. 7812, pp. 48–55. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-37210-0_6

    Chapter  Google Scholar 

  4. de Montjoye, Y.-A., Smoreda, Z., Trinquart, R., Ziemlicki, C., Blondel, V.: D4D-Senegal: The Second Mobile Phone Data for Development Challenge (2014)

    Google Scholar 

  5. de Oliveira, R., et al.: Towards a psychographic user model from mobile phone usage. In: Proceedings of the 2011 Annual Conference Extended Abstracts on Human Factors in Computing Systems. ACM (2011)

    Google Scholar 

  6. Chittaranjan, G., Blom, J., Gatica-Perez, D.: Who’s who with big-five: analyzing and classifying personality traits with smartphones. In: Proceedings of the 2011 15th Annual International Symposium on Wearable Computers (ISWC 2011). IEEE Computer Society, Washington, pp. 29–36 (2011). https://doi.org/10.1109/ISWC.2011.29

  7. Harari, G.M., Lane, N.D., Wang, R., Crosier, B.S., Campbell, A.T., Gosling, S.D.: Using smartphones to collect behavioral data in psychological science: opportunities, practical considerations, and challenges. Perspect. Psychol. Sci.: J. Assoc. Psychol. Sci. 11(6), 838–854 (2016). https://doi.org/10.1177/1745691616650285

    Article  Google Scholar 

  8. Hoang, D.T.A., Ngo, N.S., Nguyen, B.T.: Collective cubing platform towards definition and analysis of warehouse cubes. In: Nguyen, N.-T., Hoang, K., Jȩdrzejowicz, P. (eds.) ICCCI 2012. LNCS (LNAI), vol. 7654, pp. 11–20. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-34707-8_2

    Chapter  Google Scholar 

  9. Hoang, A.D.T., Nguyen, T.B.: An integrated use of CWM and ontological modeling approaches towards ETL Processes. In: ICEBE 2008, pp. 715–720 (2008)

    Google Scholar 

  10. Hoang, A.D.T., Nguyen, T.B.: State of the art and emerging rule-driven perspectives towards service-based business process interoperability. In: RIVF 2009, pp. 1–4 (2009)

    Google Scholar 

  11. Oberlander, J., Nowson, S.: Whose thumb is it anyway? Classifying author personality from weblog text. In: Proceedings of the COLING/ACL on Main Conference Poster Sessions (COLING-ACL 2006), pp. 627–634. Association for Computational Linguistics, Stroudsburg (2006)

    Google Scholar 

  12. McCrae, R.R., John, O.P.: An introduction to the five-factor model and its applications. J. Pers. 60(2), 175–215 (1992)

    Article  Google Scholar 

  13. Mount, M., Ilies, R., Johnson, E.: Relationship of personality traits and counterproductive work behaviors: the mediating effects of job satisfaction. Pers. Psychol. 59, 591–622 (2006). https://doi.org/10.1111/j.1744-6570.2006.00048.x

    Article  Google Scholar 

  14. Nguyen, T.B., Dang, N.D., Nguyen, T.T.H., Ha, T.T., Phan, T.H.L., Truong, D.H.: Tracking Big5 traits based on mobile user log data. In: The 7th International Conference on Frontiers of Intelligent Computing: Theory And Application (FICTA 2018). Advances in Intelligent Systems and Computing (2018)

    Google Scholar 

  15. Nguyen, T.B., Ngo, N.S.: Semantic cubing platform enabling interoperability analysis among cloud-based linked data cubes. In: Proceedings of the 8th International Conference on Research and Practical Issues of Enterprise Information Systems, CONFENIS 2014. ACM International Conference Proceedings Series (2014)

    Google Scholar 

  16. Nguyen, T.B., Tjoa, A.M., Wagner, R.: Conceptual multidimensional data model based on metacube. In: Yakhno, T. (ed.) ADVIS 2000. LNCS, vol. 1909, pp. 24–33. Springer, Heidelberg (2000). https://doi.org/10.1007/3-540-40888-6_3

    Chapter  Google Scholar 

  17. Nguyen, T.B., Wagner, F.: Collective intelligent toolbox based on linked model framework. J. Intell. Fuzzy Syst. 27(2), 601–609 (2014)

    MathSciNet  Google Scholar 

  18. Nguyen, T.B., Wagner, F., Schoepp, W.: Federated data warehousing application framework and platform-as-a-services to model virtual data marts in the clouds. Int. J. Intell. Inf. Database Syst. 8(3), 280 (2014). https://doi.org/10.1504/ijiids.2014.066635. ISSN 1751-5858, 1751-5866

    Article  Google Scholar 

  19. Nguyen, T.B., Wagner, F., Schoepp, W.: EC4MACS – an integrated assessment toolbox of well-established modeling tools to explore the synergies and interactions between climate change, air quality and other policy objectives. In: Auweter, A., Kranzlmüller, D., Tahamtan, A., Tjoa, A.M. (eds.) ICT-GLOW 2012. LNCS, vol. 7453, pp. 94–108. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-32606-6_8

    Chapter  Google Scholar 

  20. Nguyen, T.B., Wagner, F., Schoepp, W.: GAINS-BI: business intelligent approach for greenhouse gas and air pollution interactions and synergies information system. In: Proceedings of the International Organization for Information Integration and Web-Based Application and Services IIWAS 2008, Linz (2008)

    Google Scholar 

  21. Peng, K.-H., Liou, L.-H., Chang, C.-S., Lee, D.-S.: Predicting personality traits of Chinese users based on Facebook wall posts, pp. 9–14 (2015). https://doi.org/10.1109/wocc.2015.7346106

  22. Tomlinson, M.T., Hinote, D., Bracewell, D.B.: Predicting conscientiousness through semantic analysis of facebook posts. In: Proceedings of Workshop on Computational Personality Recognition. AAAI Press, Melon Park (2013)

    Google Scholar 

  23. Zhang, W., Gao, F.: An improvement to Naive Bayes for text classification. Proc. Eng. 15, 2160–2164 (2011). https://doi.org/10.1016/j.proeng.2011.08.404. ISSN 1877-7058

    Article  Google Scholar 

  24. https://en.wikipedia.org/wiki/Bayes%27_theorem

  25. https://en.wikipedia.org/wiki/Big_Five_personality_traits

  26. https://en.wikipedia.org/wiki/Naive_Bayes_classifier

  27. https://vaciniti.com/mobile-phone-users-worldwide/

Download references

Acknowledgement

Thanks to Orange Sonatel Senegal and the D4D team for providing the mobile phone data. Support from the Duy Tan University, Vietnam is acknowledged.

Author information

Authors and Affiliations

  1. Duy Tan University, Danang, Vietnam

    Binh Thanh Nguyen & Dang Ngoc Dung

Authors
  1. Binh Thanh Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dang Ngoc Dung
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Binh Thanh Nguyen .

Editor information

Editors and Affiliations

  1. Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Ngoc Thanh Nguyen

  2. Bina Nusantara University, Jakarta, Indonesia

    Ford Lumban Gaol

  3. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Nguyen, B.T., Dung, D.N. (2019). Big5 Tool for Tracking Personality Traits. In: Nguyen, N., Gaol, F., Hong, TP., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2019. Lecture Notes in Computer Science(), vol 11431. Springer, Cham. https://doi.org/10.1007/978-3-030-14799-0_62

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-14799-0_62

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14798-3

  • Online ISBN: 978-3-030-14799-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation