Deep Analytics Based on Triathlon Athletes’ Blogs and News

  • Iztok FisterJr.Email author
  • Dušan Fister
  • Samo Rauter
  • Uroš Mlakar
  • Janez Brest
  • Iztok Fister
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 837)


Studying the lifestyle of various groups of athletes has been a very interesting research direction of many social sport scientists. Following the behavior of these athletes’ groups might reveal how they work, yet function in the real-world. Triathlon is basically depicted as one of the hardest sports in the world (especially long-distance triathlons). Hence, studying this group of people can have a very positive influence on designing new perspectives and theories about their lifestyle. Additionally, the discovered information also helps in designing modern systems for planning sport training sessions. In this paper, we apply deep analytic methods for discovering knowledge from triathlon athletes’ blogs and news posted on their websites. Practical results reveal that triathlon remains in the forefront of the athletes’ minds through the whole year.


Artificial Sport Trainer Data mining Data science Lifestyle Triathletes Websites 


  1. 1.
    Bird, S., Klein, E., Loper, E.: Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit. O’Reilly Media, Inc., Sebastopol (2009)zbMATHGoogle Scholar
  2. 2.
    Bridel, W.F.: Finish whatever it takes considering pain and pleasure in the Ironman Triathlon: a socio-cultural analysis. Ph.D thesis. Queens University (2010)Google Scholar
  3. 3.
    Fister Jr., I., Ljubič, K., Suganthan, P.N., Perc, M., Fister, I.: Computational intelligence in sports: challenges and opportunities within a new research domain. Appl. Math. Comput. 262, 178–186 (2015)MathSciNetGoogle Scholar
  4. 4.
    Green, B.C., Jones, I.: Serious leisure, social identity and sport tourism. Sport in Soc. 8(2), 164–181 (2005)CrossRefGoogle Scholar
  5. 5.
    Knechtle, B., Nikolaidis, P.T., Rosemann, T., Rüst, C.A.: Der Ironman-Triathlon. Praxis (16618157) 105(13), 761–773 (2016)CrossRefGoogle Scholar
  6. 6.
    Rauter, S.: Mass sports events as a way of life (differences between the participants in a cycling and a running event). Kinesiol. Slov. 20(1), 5 (2014)Google Scholar
  7. 7.
    Richard, S., Jones, I.: The great suburban Everest: an insiders perspective on experiences at the 2007 Flora London Marathon. J. Sport Tour. 13(1), 61–77 (2008)CrossRefGoogle Scholar
  8. 8.
    Shipway, R., Holloway, I.: Running free: embracing a healthy lifestyle through distance running. Perspect. Public Health 130(6), 270–276 (2010)CrossRefGoogle Scholar
  9. 9.
    Sokol, L., Chan, S.: Context-based analytics in a big data world: better decisions. IBM Redbooks (2013)Google Scholar
  10. 10.
    Stebbins, R.A.: Serious Leisure: A Perspective for our Time, vol. 95. Transaction Publishers, Piscataway (2007)Google Scholar
  11. 11.
    Wicker, P., Hallmann, K., Prinz, J., Weimar, D.: Who takes part in triathlon? An application of lifestyle segmentation to triathlon participants. Int. J. Sport Manage. Mark. 12(1–2), 1–24 (2012)Google Scholar
  12. 12.
    Willig, C.: A phenomenological investigation of the experience of taking part in extreme sports’. J. Health Psychol. 13(5), 690–702 (2008)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Iztok FisterJr.
    • 1
    Email author
  • Dušan Fister
    • 2
  • Samo Rauter
    • 3
  • Uroš Mlakar
    • 1
  • Janez Brest
    • 1
  • Iztok Fister
    • 1
  1. 1.Faculty of Electrical Engineering and Computer ScienceUniversity of MariborMariborSlovenia
  2. 2.Faculty of Mechanical EngineeringUniversity of MariborMariborSlovenia
  3. 3.Faculty of SportUniversity of LjubljanaLjubljanaSlovenia

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