Advertisement

Visualization of Users Raking in Online Dating Service

  • Jana NowakováEmail author
  • Martin Hasal
  • Václav Snášel
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1035)

Abstract

Data visualization represents an important tool in data analysis. In this paper, we focus on the visualization of data from online dating service - Libimseti. Libimseti is a rarity among online dating services because it offers a user’s raking system. It means that every user can evaluate other users on the scale from one to ten.

We present a modification of a circular plot to represent general data from the raking system. The introduced visualization provides both aesthetically pleasing and readable graph. It shows a general overview of people’s behavior, opinion, and personal preferences in the given service without deeper understating of the data.

It helps to discover users who can suffer from other users negativity or users who provoke others and decrease the popularity of the web itself. Moreover, the presented graph can help to find influencers, who can popularize the website among its users.

Keywords

Data visualization Online dating service Rating Anomaly detection 

Notes

Acknowledgements

This work was supported by the European Regional Development Fund under the project AI&Reasoning (reg. no. CZ.02.1.01/0.0/0.0/15_003/0000466), by the Technology Agency of the Czech Republic under the grant no. TN01000024, and by the project SP2019/135 of the Student Grant System, VŠB-Technical University of Ostrava.

References

  1. 1.
    Al Hasib, A.: Threats of online social networks. IJCSNS Int. J. Comput. Sci. Netw. Secur. 9(11), 288–93 (2009)Google Scholar
  2. 2.
    Brozovsky, L., Petricek, V.: Recommender system for online dating service. In: Proceedings of Conference Znalosti 2007, VSB, Ostrava (2007). http://www.occamslab.com/petricek/papers/dating/brozovsky07recommender.pdf
  3. 3.
    Buyukkokten, O., Smith, A.D.: Methods and systems for rating associated members in a social network (2011). US Patent 8,010,459Google Scholar
  4. 4.
    Chen, C.H., Hrdle, W., Unwin, A., Chen, C.H., Hrdle, W., Unwin, A.: Handbook of Data Visualization (Springer Handbooks of Computational Statistics), 1 edn. Springer, Heidelberg (2008)Google Scholar
  5. 5.
    Chen, I.X., Yang, C.Z.: Visualization of Social Networks, pp. 585–610. Springer, Boston (2010).  https://doi.org/10.1007/978-1-4419-7142-5_27
  6. 6.
    Fiore, A.R.T.: Romantic regressions: an analysis of behavior in online dating systems. Ph.D. thesis, Massachusetts Institute of Technology (2004)Google Scholar
  7. 7.
    Gewirtz-Meydan, A., Ayalon, L.: Forever young: visual representations of gender and age in online dating sites for older adults. J. Women Aging 30(6), 484–502 (2018)CrossRefGoogle Scholar
  8. 8.
    Ji, J.J.: Method and system for online collaborative ranking and reviewing of classified goods or services (2008). US Patent App. 11/952,562Google Scholar
  9. 9.
    Langville, A.N., Meyer, C.D.: Who’s #1?: The Science of Rating and Ranking. Princeton University Press, Princeton (2012)CrossRefGoogle Scholar
  10. 10.
    Leonard, M.: Matching social network users (2011). US Patent 8,060,573Google Scholar
  11. 11.
    Merkle, E.R., Richardson, R.A.: Digital dating and virtual relating: conceptualizing computer mediated romantic relationships. Family Relat. 49(2), 187–192 (2000)CrossRefGoogle Scholar
  12. 12.
    Rege, A.: What’s love got to do with it? Exploring online dating scams and identity fraud. Int. J. Cyber Criminol. 3(2), 494–512 (2009)Google Scholar
  13. 13.
    Toma, C.L., Hancock, J.T., Ellison, N.B.: Separating fact from fiction: an examination of deceptive self-presentation in online dating profiles. Pers. Soc. Psychol. Bull. 34(8), 1023–1036 (2008).  https://doi.org/10.1177/0146167208318067. PMID: 18593866
  14. 14.
    Weisbuch, M., Ivcevic, Z., Ambady, N.: On being liked on the web and in the “real world”: consistency in first impressions across personal webpages and spontaneous behavior. J. Exp. Soc. Psychol. 45(3), 573–576 (2009)CrossRefGoogle Scholar
  15. 15.
    Yang, Y.: Method and apparatus for evaluating trust and transitivity of trust of online services (2007). US Patent 7,249,380Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Jana Nowaková
    • 1
    Email author
  • Martin Hasal
    • 2
  • Václav Snášel
    • 1
  1. 1.Department of Computer ScienceVŠB – Technical University of OstravaOstrava, PorubaCzech Republic
  2. 2.IT4InnovationsVŠB – Technical University of OstravaOstrava, PorubaCzech Republic

Personalised recommendations