IDEAS home Printed from
   My bibliography  Save this article

Social network sites: What users post and to whom they address. Some approaches to the study


  • Kotyrlo , Elena

    () (National Research University Higher School of Economics (NRU HSE), Moscow, Russian Federation;)


Study of users and their segmentation, based on users’ preferred topics of discussion and their networking, is the unique opportunity offered by social networks. Variety of approaches to social media analysis based on social network analysis and text mining is summarized in the paper. It is extended by concentration index application and visualizing of the results of social network analysis. The study of a model set exhibits that: 1) users can be successfully segmented on the base of their most mentioned topics, which is useful for a product placement and other commercial purposes; 2) distribution of number of posts by authors is highly uneven regardless to the topic of discussion; 3) users connected on-line typically live in the same geographical area; 4) users’ number of posts and centrality indices are correlated.

Suggested Citation

  • Kotyrlo , Elena, 2017. "Social network sites: What users post and to whom they address. Some approaches to the study," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 47, pages 74-99.
  • Handle: RePEc:ris:apltrx:0325

    Download full text from publisher

    File URL:
    File Function: Full text
    Download Restriction: no

    References listed on IDEAS

    1. Gert Sabidussi, 1966. "The centrality index of a graph," Psychometrika, Springer;The Psychometric Society, vol. 31(4), pages 581-603, December.
    2. Goodreau, Steven M. & Handcock, Mark S. & Hunter, David R. & Butts, Carter T. & Morris, Martina, 2008. "A statnet Tutorial," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i09).
    3. Feinerer, Ingo & Hornik, Kurt & Meyer, David, 2008. "Text Mining Infrastructure in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i05).
    4. Ivan Smirnov & Elizaveta Sivak & Yana Kozmina, 2016. "In Search of Lost Profiles: The Reliability of VKontakte Data and Its Importance for Educational Research," Educational Studies, Higher School of Economics, issue 4, pages 106-122.
    Full references (including those not matched with items on IDEAS)

    More about this item


    text mining; social network analysis; social network sites; regression analysis; Gini coefficient.;

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • M39 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Other


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:apltrx:0325. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Anatoly Peresetsky). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.