An Efficient Facebook Place Information Extraction Strategy

  • Jong-Shin Chen
  • Chuan-Bi Lin
  • Cheng-Ying Yang
  • Yung-Fa HuangEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 971)


Facebook is an online social media and social networking service, which is most popular in the world. Location-based Facebook check-in service is a hot topic. Facebook users go to their interested check-in places and check in there. Numerous check-in behaviors at these places can form public options, for example hot places, high density regions. Therefore, information extraction of Facebook places can provide significant meanings such as business market decision or population traffic. However, few studies are based on it as the research field. These studies always are based on Foursquare as the research field. One of the major reasons is that Facebook platform only allows limited data access. Numerous places and check-in behaviors at these places can form public options for example hot places, high-density regions of places. In this study, we present a method to collect the big data of Facebook check-in places. Facebook penetration rate in Taiwan is the highest in the world. Moreover, there are many Facebook places in Taiwan are created related to delicacy food. Taiwanese “beef noodle”, Japanese “Sushi”, and Korean “Kimchi” all are popular in the world and in Taiwan. Accordingly, in this study, we use these as example to find out the related places, individually.


Facebook place Check-in Public option Beef noodle Kimchi 


  1. 1.
    Wikipedia (2017). Accessed 5 Mar 2017
  2. 2.
    Wikipedia. Accessed 5 Mar 2017
  3. 3.
    Wikipedia. Accessed 5 Mar 2017
  4. 4.
    Wikipedia. Accessed 5 Mar 2017
  5. 5.
    Bawa-Cavia, A.: Sensing the urban: using location-based social network data in urban analysis. In: First Workshop on Pervasive Urban Applications (PURBA), San Francisco (2010)Google Scholar
  6. 6.
    Cheng, Z., Caverlee, J., Lee, K., Sui, D.: Exploring millions of footprints in location sharing services. In: Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, Barcelona (2011)Google Scholar
  7. 7.
    Crandall, D.J., Backstrom, L., Cosley, D., Suri, S., Huttenlocher, D., Kleinberg, J.: Inferring social ties from geographic coincidences. Proc. Natl. Acad. Sci. 107(52), 22436–22441 (2010)CrossRefGoogle Scholar
  8. 8.
    Cranshaw, J., Schwartz, R., Hong, J., Sadeh, N.: The livehoods project: utilizing social media to understand the dynamics of a city. In: Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media, Dublin (2012)Google Scholar
  9. 9.
  10. 10.
  11. 11.
    Chen, J.S., et al.: Public option analysis for hot check-in places at Taiwan. In: International Conference on Advanced Information Technologies, pp. 745–755, Taiwan (2017)Google Scholar
  12. 12.
    Kotenko, I., Kolomeets, M., Chechulin, A., Chevalier, Y.: A visual analytics approach for the cyber forensics based on different views of the network traffic. J. Wirel. Mob. Netw. Ubiquitous Comput. Dependable Appl. (JoWUA) 9(2), 57–73 (2018)Google Scholar
  13. 13.
    Kotenko, I., Saenko, I., Kushnerevich, A.: Parallel big data processing system for security monitoring in Internet of Things networks. J. Wirel. Mob. Netw. Ubiquitous Comput. Dependable Appl. (JoWUA) 8(4), 60–74 (2017)Google Scholar
  14. 14.
    Kotenko, I., Saenko, I., Branitskiy, A.: Applying big data processing and machine learning methods for mobile internet of things security monitoring. J. Internet Services Inf. Secur. (JISIS) 8(3), 54–63 (2018)Google Scholar
  15. 15.
    Lim, K., Jeong, Y., Cho, S.-J., Park, M., Han, S.: An android application protection scheme against dynamic reverse engineering attacks. J. Wirel. Mob. Netw. Ubiquitous Comput. Dependable Appl. (JoWUA) 7(3), 40–52 (2016)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Jong-Shin Chen
    • 1
  • Chuan-Bi Lin
    • 1
  • Cheng-Ying Yang
    • 2
  • Yung-Fa Huang
    • 1
    Email author
  1. 1.Department of Information and Communication EngineeringChaoyang University of TechnologyWufeng, TaichungTaiwan, R.O.C.
  2. 2.Department of Computer ScienceUniversity of TaipeiTaipeiTaiwan, R.O.C.

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