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The Use of Social Computing in Travelers’ Activities Preference Analysis

  • Charis ChalkiadakisEmail author
  • Panagiotis Iordanopoulos
  • Evangelos Mitsakis
  • Eleni Chalkia
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 879)

Abstract

Each traveler moves across the physical plane to perform activities. It is known that each trip connects two distinct activities. Travelers, during their trips, make various choices in order to decide mode, route and time of departure. These choices depend on factors that are either predetermined or emotional. Other factors such as existence of various events can also affect the choices of the travelers. During the last decade, information related to the factors mentioned above, are addressed through the social networks. The amount of information provided in the social media is important and crucial in addressing the way travelers move around. On the other hand, understanding and, more importantly, predicting activities is a crucial matter in order to predict traffic conditions as well as to provide improved trip advice to travelers.

The present paper studies the possibilities and capabilities exist in order to proceed to transport modelling techniques by deriving information from the social media status updates of the users. More specifically the study reviews methodologies and techniques that can collect information from the users’ status updates in order to estimate their preferences.

In the present study the development of a methodology which integrates the gathered information from the social media status updates with stated activities’ preferences is being investigated. The review takes into account the social computing paradigm where humans and machines collaborate to solve a social problem. Also, multiple data sources are examined in order more integrated results to be returned.

Keywords

Social computing Travelers activities Social media Data collection 

Notes

Acknowledgement

The present paper presents the findings of the literature review and the proposed methodology conducted within the framework of My-TRAC Project (funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 777640).

References

  1. 1.
    Parameswaran, M., Whinston, A.B.: Social computing: an overview. Commun. Assoc. Inf. Syst. 19, Article 37, 762–780 (2007).  https://doi.org/10.17705/1CAIS.01937
  2. 2.
    Hanna, R., Rohm, A., Crittenden, V.L.: We’re all connected: the power of the social media ecosystem. Bus. Horiz. 54, 265–273 (2011).  https://doi.org/10.1016/j.bushor.2011.01.007CrossRefGoogle Scholar
  3. 3.
    Rashidi, T.H., Abbasi, A., Maghrebi, M., Hasan, S., Waller, T.S.: Exploring the capacity of social media data for modelling travel behaviour: opportunities and challenges. Transp. Res. Part C Emerg. Technol. 75, 197–211 (2017).  https://doi.org/10.1016/j.trc.2016.12.008CrossRefGoogle Scholar
  4. 4.
    Facebook. www.facebook.com. Accessed 21 Jan 2018
  5. 5.
    Twitter. www.twitter.com. Accessed 21 Jan 2018
  6. 6.
    Foursquare. https://foursquare.com/. Accessed 21 Jan 2018
  7. 7.
    Chaniotakis, E., Antoniou, C., Pereira, F.: Mapping social media for transportation studies. IEEE Intell. Syst. 31, 64–70 (2016).  https://doi.org/10.1109/MIS.2016.98CrossRefGoogle Scholar
  8. 8.
    Zheng, X., Chen, W., Wang, P., Shen, D., Chen, S., Wang, X., Zhang, Q., Yang, L.: Big data for social transportation. IEEE Trans. Intell. Transp. Syst. 17, 620–630 (2015).  https://doi.org/10.1109/TITS.2015.2480157CrossRefGoogle Scholar
  9. 9.
    D’Andrea, E., Ducange, P., Lazzerini, B., Marcelloni, F.: Real-time detection of traffic from Twitter stream analysis. IEEE Trans. Intell. Transp. Syst. 16, 2269–2283 (2015).  https://doi.org/10.1109/TITS.2015.2404431CrossRefGoogle Scholar
  10. 10.
    Gal-Tzur, A., Grant-Muller, S.M., Kuflik, T., Minkov, E., Nocera, S., Shoor, I.: The potential of social media in delivering transport policy goals. Transp. Policy 32, 115–123 (2014).  https://doi.org/10.1016/j.tranpol.2014.01.007CrossRefGoogle Scholar
  11. 11.
    Kuflik, T., Minkov, E., Nocera, S., Grant-Muller, S., Gal-Tzur, A., Shoor, I.: Automating a framework to extract and analyse transport related social media content: the potential and the challenges. Transp. Res. Part C Emerg. Technol. 77, 275–291 (2017).  https://doi.org/10.1016/j.trc.2017.02.003CrossRefGoogle Scholar
  12. 12.
    Ruiz, T., Mars, L., Arroyo, R., Serna, A.: Social networks, big data and transport planning. Transp. Res. Procedia 18, 446–452 (2016).  https://doi.org/10.1016/j.trpro.2017.01.122CrossRefGoogle Scholar
  13. 13.
    Wanichayapong, N., Pruthipunyaskul, W., Pattara-Atikom, W., Chaovalit, P.: Social-based traffic information extraction and classification. In: International Conference on ITS Telecommununications, pp. 107–112 (2011).  https://doi.org/10.1109/itst.2011.6060036
  14. 14.
    Chaniotakis, E., Antoniou, C., Aifadopoulou, G., Dimitriou, L.: Inferring activities from social media data. In: 96th Annual Meet Transportation Research Board, pp. 1–8 (2016).  https://doi.org/10.3141/2666-04
  15. 15.
    Chaniotakis, E., Antoniou, C.: Use of geotagged social media in urban settings: empirical evidence on its potential from Twitter. In: IEEE Conference on Intelligent Transport System Proceedings, ITSC 2015, pp. 214–219 (2015).  https://doi.org/10.1109/itsc.2015.44
  16. 16.
    Sinha, M., Varma, P., Sivakumar, G., Singh, M., Mukherjee, T., Chander, D., Dasgupta, K.: Improving urban transportation through social media analytics. In: Proceedings of the 3rd IKDD Conference on Data Science, CODS 2016, pp. 1–2 (2016)Google Scholar
  17. 17.
    Chaniotakis, E., Antoniou, C., Mitsakis, E.: Data for leisure travel demand from social networking services. In: Heart Conference (2015)Google Scholar
  18. 18.
    Twitter API. https://developer.twitter.com/. Accessed 21 Jan 2018
  19. 19.
    Efthymiou, D., Antoniou, C.: Use of social media for transport data collection. Procedia Soc. Behav. Sci. 48, 775–785 (2012).  https://doi.org/10.1016/j.sbspro.2012.06.1055CrossRefGoogle Scholar
  20. 20.
    Cottrill, C., Gault, P., Yeboah, G., Nelson, J.D., Anable, J., Budd, T.: Tweeting transit: an examination of social media strategies for transport information management during a large event. Transp. Res. Part C Emerg. Technol. 77, 421–432 (2017).  https://doi.org/10.1016/j.trc.2017.02.008CrossRefGoogle Scholar
  21. 21.
    The R Project for Statistical Computing. https://www.r-project.org/. Accessed 21 Jan 2018
  22. 22.
    TwitterXML. https://twitterxml.codeplex.com/. Accessed 21 Jan 2018
  23. 23.
    TwitterXML BlogSpot. http://twitterxml.blogspot.gr/. Accessed 21 Jan 2018
  24. 24.
    Toumpalidis, I.: Physical Spaces and Digital Flows: Navigating through the Informational Matrix, A dissertation submitted in partial fulfillment of the requirements for the degree of Master of Research of Spatial Data Science and Visualisation. The Bartlett Centre for Advanced Spatial Analysis University College London (2017)Google Scholar
  25. 25.
    Toumpalidis, I., Karanikolas, N.: Spatial Data Mining from Social Media Services. Aristotle University of Thessaloniki (2015)Google Scholar
  26. 26.
    Toumpalidis, I., Karanikolas, N.: Spatial Data Analysis from Social Media Services, Research study, School of Planning and Development. Aristotle University of Thessaloniki (2015)Google Scholar
  27. 27.
    Grau, J.M.S., Toumpalidis, I., Chaniotakis, E., Karanikolas, N., Aifadopoulou, G.: A spatio-temporal correlation between digital and physical world, case study in Thessaloniki (under review)Google Scholar
  28. 28.
    Grau, J.M.S., Chaniotakis, E., Toumpalidis, I., Karanikolas, N., Aifadopoulou, G.: Big data for transportation analysis and trip generation (under review)Google Scholar
  29. 29.
    Facebook API. https://developers.facebook.com/. Accessed 21 Jan 2018
  30. 30.
    Cambridge Dictionary. https://dictionary.cambridge.org/dictionary/english/trend. Accessed 21 Jan 2018

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Charis Chalkiadakis
    • 1
    Email author
  • Panagiotis Iordanopoulos
    • 1
  • Evangelos Mitsakis
    • 1
  • Eleni Chalkia
    • 1
  1. 1.Hellenic Institute of Transport – Centre for Research and Technology HellasThermi, ThessalonikiGreece

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