Journal article Open Access

From risk factors to detection and intervention: a practical proposal for future work on cyberbullying

Andri Ioannou; Jeremy Blackburn; Gianluca Stringhini; Emiliano De Cristofaro; Nicolas Kourtellis; Michael Sirivianos


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    <subfield code="a">internet bullying</subfield>
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    <subfield code="a">cyber aggression</subfield>
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    <subfield code="u">University of Alabama at Birmingham</subfield>
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    <subfield code="u">University College London</subfield>
    <subfield code="a">Gianluca Stringhini</subfield>
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    <subfield code="u">University College London</subfield>
    <subfield code="a">Emiliano De Cristofaro</subfield>
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    <subfield code="u">Telefonica Research</subfield>
    <subfield code="a">Nicolas Kourtellis</subfield>
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    <subfield code="u">Cyprus Interaction Lab</subfield>
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    <subfield code="c">Pages 258-266</subfield>
    <subfield code="n">Issue 3</subfield>
    <subfield code="p">Behaviour &amp; Information Technology</subfield>
    <subfield code="v">Volume 37</subfield>
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    <subfield code="u">Cyprus Interaction Lab</subfield>
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    <subfield code="a">Andri Ioannou</subfield>
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    <subfield code="a">From risk factors to detection and intervention: a practical proposal for future work on cyberbullying</subfield>
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    <subfield code="a">&lt;p&gt;While there is an increasing flow of media stories reporting cases of cyberbullying, particularly within&lt;br&gt;
online social media, research efforts in the academic community are scattered over different topics&lt;br&gt;
across the social science and computer science academic disciplines. In this work, we explored&lt;br&gt;
research pertaining to cyberbullying, conducted across disciplines. We mainly sought to&lt;br&gt;
understand scholarly activity on intelligence techniques for the detection of cyberbullying when it&lt;br&gt;
occurs. Our findings suggest that the vast majority of academic contributions on cyberbullying&lt;br&gt;
focus on understanding the phenomenon, risk factors, and threats, with the prospect of&lt;br&gt;
suggesting possible protection strategies. There is less work on intelligence techniques for the&lt;br&gt;
detection of cyberbullying when it occurs, while currently deployed algorithms seem to detect&lt;br&gt;
the problem only up to some degree of success. The article summarises the current trends aiming&lt;br&gt;
to encourage discussion and research with a new scope; we call for more research tackling the&lt;br&gt;
problem by leveraging statistical models and computational mechanisms geared to detect,&lt;br&gt;
intervene, and prevent cyberbullying. Coupling intelligence techniques with specific web&lt;br&gt;
technology problems can help combat this social menace. We argue that a multidisciplinary&lt;br&gt;
approach is needed, with expertise from human&amp;ndash;computer interaction, psychology, computer&lt;br&gt;
science, and sociology, for current challenges to be addressed and significant progress to be made.&lt;/p&gt;</subfield>
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    <subfield code="a">10.1080/0144929X.2018.1432688</subfield>
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