Implicit Location Sharing Detection in Social Media Turkish Text Messaging

  • Davut Deniz Yavuz
  • Osman AbulEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10122)


Social media have become a significant venue for information sharing of live updates. Users of social media are producing and sharing large amount of personal data as a part of the live updates. A significant share of this data contains location information that can be used by other people for many purposes. Some of the social media users deliberately share their own location information with other users. However, a large number of users blindly or implicitly share their own location without noticing it and its possible consequences. Implicit location sharing is investigated in the current paper.

We perform a large scale study on implicit location sharing detection for one of the most popular social media platform, namely Twitter. After a careful study, we prepared a training data set of Turkish tweets and manually labelled them. Using machine learning techniques we induced classifiers that are able to classify whether a given tweet contains implicit location sharing or not. The classifiers are shown to be very accurate and efficient as well. Moreover, the best classifier is employed in a browser add-on tool which warns the user whenever an implicit location sharing is predicted from just to be released tweet. The paper provides the followed methodology and the technical analysis as well. Furthermore, it discusses how these techniques can be extended to different social network services and also to different languages.


Location privacy Social media Machine learning 


  1. 1.
    Shin, K.G., Ju, X., Chen, Z., Hu, X.: Privacy protection for users of location-based services. IEEE Wirel. Commun. 19(1), 30–39 (2012)CrossRefGoogle Scholar
  2. 2.
    Pandarachalil, R., Sendhilkumar, S., Mahalakshmi, G.S.: Twitter sentiment analysis for large-scale data: an unsupervised approach. Cogn. Comput. 7(2), 254–262 (2015)CrossRefGoogle Scholar
  3. 3.
    Agarwal, A., Xie, B., Vovsha, I., Rambow, O., Passonneau, R.: Sentiment analysis of Twitter data. In: Proceedings of the Workshop on Languages in Social Media (LSM 2011), Stroudsburg, PA, USA, pp. 30–38 (2011)Google Scholar
  4. 4.
    Ajao, O., Hong, J., Liu, W.: A survey of location inference techniques on Twitter. J. Inf. Sci. 41(6), 855–864 (2015)CrossRefGoogle Scholar
  5. 5.
    Cheng, Z., Caverlee, J., Lee, K.: You are where you tweet: a contentbased approach to geo-locating Twitter users. In: Proceedings of CIKM 2010, Toronto, Canada, pp. 759–768 (2010)Google Scholar
  6. 6.
    Jurgens, D.: That’s what friends are for: inferring location in online social media platforms based on social relationships. In: Proceedings of ICWSM 2013, Boston, MA, pp. 273–282 (2013)Google Scholar
  7. 7.
    Taslioglu, H.: Irony detection on Turkish microblog texts. Master thesis, Middle East Technical University, Ankara (2014)Google Scholar
  8. 8.
    Stefanidis, A.: Harvesting ambient geospatial information from social media feeds (2012).
  9. 9.
    Kadaba, L.S.: What is privacy? As job-seekers are judged by their tweets and Facebook posts, uncertainty abounds (2012).
  10. 10.
    Pontes, T.: Beware of what you share inferring home location in social networks. In: IEEE 12th International Conference on Data Mining Workshops, Brussels, Belgium, pp. 571–578 (2012)Google Scholar
  11. 11.
    Foursquare: Privacy 101 (2016).
  12. 12.
    Weidemann, C.: (2013).
  13. 13.
    Weidemann, C.: Social Media Location Intelligence: The Next Privacy Battle - An ArcGIS add-in and Analysis of Geospatial Data Collected from (2013).
  14. 14.
    Groeveneld, F., Borsboom, B., Amstel, B.: Over-sharing and Location Awareness (2011).
  15. 15.
    Twitter: Twitter Privacy Policy (2016).
  16. 16.
  17. 17.
    Twitter developer.
  18. 18.
  19. 19.
    Official Turkish Dictionary.
  20. 20.
  21. 21.

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Department of Computer EngineeringTOBB University of Economics and TechnologyAnkaraTurkey

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