Journal article Open Access

Associating Facebook Measurable Activities with Personality Traits: A Fuzzy Sets Approach

Nikolaos Misirlis; George Lekakos; Maro Vlachopoulou


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        <foaf:name>Nikolaos Misirlis</foaf:name>
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        <foaf:name>George Lekakos</foaf:name>
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        <foaf:name>Maro Vlachopoulou</foaf:name>
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    <dct:title>Associating Facebook Measurable Activities with Personality Traits: A Fuzzy Sets Approach</dct:title>
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    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2018</dct:issued>
    <dcat:keyword>Big Five</dcat:keyword>
    <dcat:keyword>fsQCA</dcat:keyword>
    <dcat:keyword>Facebook</dcat:keyword>
    <dcat:keyword>personality traits</dcat:keyword>
    <dcat:keyword>Facebook measurements</dcat:keyword>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2018-11-15</dct:issued>
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    <dct:description>&lt;p&gt;&lt;em&gt;In this study we identify potential associations between people&amp;rsquo;s personality (utilizing the popular Big Five personality model) and measurable Facebook activities such as number of likes received, number of posts, number of comments on posts. Extant literature suggests that personality can be manifested through different features of the Facebook profiles but under an implicit assumption that those users may belong in a single psychographic group. However, it has been shown that people may share characteristics, common acts and behaviors of more than one psychographic group. In this study we aim to address limitations of previous studies, by adopting a fuzzy set approach which is capable to handle users&amp;rsquo; membership in multiple psychographic groups. Furthermore, fsQCA offers equifinality, which means that research can end up to the same outcome, beginning from different initial combinations of data. The work presented here provides empirical evidence concerning the association between Facebook activities and users&amp;#39; personalities in a novel way indicating the significance of this relationship and providing alternative combinations that lead to the same output. Furthermore, it paves the ground towards predicting social platforms&amp;#39; measurements, other than Facebook, relying on users&amp;#39; personalities, using the same technique but on different fields of study and social media platforms.&lt;/em&gt;&lt;/p&gt;</dct:description>
    <dct:description>SUBMITTED: FEBRUARY 2018; REVISION SUBMITTED: MARCH 2018; ACCEPTED: JULY 2018; REFEREED ANONYMOUSLY; PUBLISHED ONLINE: 15 NOVEMBER 2018</dct:description>
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