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Predicting responses to Czech universities' posts on Facebook

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F18%3A43913695" target="_blank" >RIV/62156489:43110/18:43913695 - isvavai.cz</a>

  • Result on the web

    <a href="http://pefnet.mendelu.cz/wcd/w-rek-pefnet/pefnet17_fin.pdf" target="_blank" >http://pefnet.mendelu.cz/wcd/w-rek-pefnet/pefnet17_fin.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Predicting responses to Czech universities' posts on Facebook

  • Original language description

    Nowadays, social networks contain huge amounts of easily available text data. This makes it a perfect source to which text mining and text analysis can be applied. The article focuses on predictions of the numbers of responses to Facebook posts on the pages of Czech universities and faculties. Machine learning classification was used as the principal tool. To achieve the goal software for downloading and analysing the necessary data and for providing results was developed. The results take the form of a percentage probability with which the number of responses to a new post can be determined. During the tests, an approximately 75% classification success rate was achieved.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    PEFnet 2017: Proceedings

  • ISBN

    978-80-7509-555-8

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    7

  • Pages from-to

    80-86

  • Publisher name

    Mendelova univerzita v Brně

  • Place of publication

    Brno

  • Event location

    Brno

  • Event date

    Nov 30, 2017

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article