Verbal Aggressiveness Exploration through Complete Social Network Analysis: Using Physical Education Students’ Class as an Illustration

Alexandra Bekiari, Nikolaos Hasanagas


Aim of this study: is a) to detect informal structures (power and position in structures of targeting of verbal aggression) among higher education students, b) to analyze determinants of these structural properties, and c) to propose a typology of verbal aggression targets. Complete network analysis was applied on a sample of a 53 students in Physical Education Faculty, Thessaly University, Greece. Four network analysis algorithms were used: in-degree, Katz status, pagerank, authority. Non-network and network determinants of being target of verbal aggressiveness were analyzed. Gender (particularly femaleness), high grade of school graduation and parents education level protect from verbal aggressiveness while interest in post-graduate study seems to provoke criticism. Ignoring public opinion and intimacy with many “close friends” are positively correlated with verbal aggressiveness. Young (and not old-fashioned) appearance, imposing and eccentric appearance characteristics seem to protect against verbal aggressiveness. Big corporal size, dark skin colors seem to provoke insults in case of female students. Eminent economic state is also provocative as it implies pretentiousness. Phone verbal aggressiveness appears mainly among male students. Eminent qualities such as “good friend”, “desirable partner” etc make someone an eminent target for verbal aggressiveness. Verbal aggressiveness presents a catholic character and thus seems to be destructive and not constructive. Intellectual abilities (weaknesses) constitute a verbal aggressiveness target core. The following types of verbal aggressiveness targets are proposed: a) the “general ‘black sheep’”, b) the “contemptible type”, c) the “bagger” type, d) the “victim of mockers” and e) the “victim of serial criticizers”.

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International Journal of Social Science Studies   ISSN 2324-8033 (Print)   ISSN 2324-8041 (Online)

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