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Publishing Patterns in Greek Media Websites

Author

Listed:
  • Evangelia Avraam

    (School of Journalism & MC, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Andreas Veglis

    (School of Journalism & MC, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Charalampos Dimoulas

    (School of Journalism & MC, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

Abstract

The concept of different publishing patterns during a day has been employed for many decades in the broadcasting industry. These patterns are close related with dayparts, which are defined as sequential time blocks on comparable days during which the audience size is homogeneous, as is the group depiction using the specific medium. During the first decade of the World Wide Web, Internet media strategy was focused on total web reach, demographics and affinity of content without particular attention to how the nature of the audience changes by time of day. This paper studies the variation of publishing patterns of the top 22 Greek media websites. More than 550 thousand articles were indexed in a period of four and a half months. The study identified distinct WWW time periods that exhibit specific publishing characteristics. Specifically, different categories of news articles present different publishing patterns during weekdays and weekends. The results appear to be in agreement with findings of previous studies.

Suggested Citation

  • Evangelia Avraam & Andreas Veglis & Charalampos Dimoulas, 2021. "Publishing Patterns in Greek Media Websites," Social Sciences, MDPI, vol. 10(2), pages 1-15, February.
    • Handle: RePEc:gam:jscscx:v:10:y:2021:i:2:p:59-:d:495709
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    References listed on IDEAS

    as
    1. João Pedro Baptista & Anabela Gradim, 2020. "Understanding Fake News Consumption: A Review," Social Sciences, MDPI, vol. 9(10), pages 1-22, October.
    2. Spann Martin & Molitor Dominik & Daurer Stephan, 2016. "Tell Me Where You Are and I’ll Tell You What You Want: Using Location Data to Improve Marketing Decisions," NIM Marketing Intelligence Review, Sciendo, vol. 8(2), pages 30-37, November.
    Full references (including those not matched with items on IDEAS)

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