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Harmonizing freedom and protection: Adolescents' voices on automatic monitoring of social networking sites

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  • Van Royen, Kathleen
  • Poels, Karolien
  • Vandebosch, Heidi

Abstract

Automatic monitoring of user-generated content on social networking sites (SNSs) aims at detecting potential harm for adolescents by means of text and image mining techniques and subsequent actions by the providers (e.g. blocking users, legal action). Evidently, current research is primarily focused on its technological development. However, involving adolescents' voices regarding the desirability of this monitoring is important; particularly because automatic monitoring might invade adolescents' privacy and freedom, and consequently evoke reactance. In this study, fourteen focus groups were conducted with adolescents (N=66) between 12 and 18years old. The goal was to obtain insights into adolescents' opinions on desirability and priorities for automatically detecting harmful content on SNSs. Opinions reflect the contention between a need for protection online versus the preservation of freedom. Most adolescents in this study are in favour of automatic monitoring for situations they perceive as uncontrollable or that they cannot solve themselves. Clear priorities for detection must be set in order to ensure the privacy and autonomy of adolescents. Moreover, monitoring actions aiming at the prevention of harm are required.

Suggested Citation

  • Van Royen, Kathleen & Poels, Karolien & Vandebosch, Heidi, 2016. "Harmonizing freedom and protection: Adolescents' voices on automatic monitoring of social networking sites," Children and Youth Services Review, Elsevier, vol. 64(C), pages 35-41.
    • Handle: RePEc:eee:cysrev:v:64:y:2016:i:c:p:35-41
    DOI: 10.1016/j.childyouth.2016.02.024
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    Cited by:

    1. Biernesser, Candice & Sewall, Craig J.R. & Brent, David & Bear, Todd & Mair, Christina & Trauth, Jeanette, 2020. "Social media use and deliberate self-harm among youth: A systematized narrative review," Children and Youth Services Review, Elsevier, vol. 116(C).
    2. Cynthia Van Hee & Gilles Jacobs & Chris Emmery & Bart Desmet & Els Lefever & Ben Verhoeven & Guy De Pauw & Walter Daelemans & Véronique Hoste, 2018. "Automatic detection of cyberbullying in social media text," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-22, October.

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