Social media Risks and Opportunities
Lecture 2: Experiencing online aggression
Online aggression: Intentional harm delivered by the use of electronic means to a person or a group of
people irrespective of their age, who perceive(s) such acts as offensive, derogatory, harmful or
unwanted (Grigg, 2010).
Cyberbullying: Bullying is an aggressive, intentional act or behaviour that is carried out by a group or
an individual repeatedly and overtime against a victim who cannot easily defend him-or herself
(Olweus, 1993) more strictly defined must happen repeatedly and an imbalance between the
victim and the perpetrator.
Growing amount of research and media attention:
- Tyler killed himself because his roommate broadcasted him with his partner making out.
- Body shaming: e.g. you’re way too thin / too thick
Who is the perpetrator
Dark Triad: Those characterized by socially offensive traits ~ Jones & Paulhus, 2014
personality traits of online aggressors (most research focussed on the big five, but not necessarily bad).
People scoring high on these dark triad traits are perceived as “cold”. People can score above or under
the mean score (not talking about extreme cases)
- Narcissism: Extreme self-involvement and therefore sometimes ignore other people. You also
find yourself unique and fantasise of success e.g. being famous. Request a lot of attention
from their surrounding e.g. special favours. They are also considered to be exploitive and
taking advantage of others.
o Often associated with social media use and especially sharing behaviour e.g. selfie
taking
- Machiavellianism: Using manipulative strategies to reach a certain goal (mostly this goal is
getting power) they think a lot about their actions and plan it. (not impulsive)
- Psychopathy: being impulsive, (if they see something they don’t like, they react immediately.
Arrogant and insensitive to the feelings of others
Closely related and some overlap between the traits (moderate correlations). But each
component is reviewed as separate
Dark triad and cyber aggression:
- Machiavellianism: associated with offline aggression among adolescents
- Narcissism: associated with offline aggression among adolescents
o Narcissist function well in online environment s (e.g. due to the controllability of self-
presentation.
o Narcistic exploitativeness: (exploitative of others, only your own interest in mind, no
moral compassion), a sub-construct of narcissism, is associated with cyber-aggression
among adolescents
- Psychopathy: associated with offline aggression and cyber aggression among adolescents
Possible exam question:
A) Facebook intensity mediates the relationship between Dark Triad personality traits and cyber-
aggression
B) Proximal determinants are immediate determinants of a specific behaviour
- Only A is correct
- Only B is correct
- Both A and B are correct
- Both A and B are false
,Possible exam question: explain the Theory of planned behaviour and apply it to an example of
online aggression
Triad personality traits and adolescent cyber-aggression ~ Pabian et al., (2015)
Investigated the relationship between the Dark Triad personality traits and cyber-aggression among
adolescents (14-18 year old) to know motives and personality profiles of online aggressors.
Distal determinants: Influence the behaviour but not in a direct way
The dark triad and cyber aggression:
Dark triad: Dark personalities; those characterized by socially offensive traits.
1. Narcissism: A sense of importance and uniqueness, fantasies of unlimited success, requesting
constant attention, expecting special favours, and being interpersonally exploitative
(Narcissists function well in online environments (E.g. due to the controllability of online self-
presentation)
a. Narcissistic exploitativeness: subconstruct: exploitative of others, only your own
interest in mind, there is no moral compassion)
2. Machiavellianism: Manipulative strategies of social conduct that are not correlated with
general intelligence, and that do not necessarily lead to success
3. Psychopathy: An impulsive behavioural style, an arrogant, deceitful interpersonal style and a
deficient affective experience
Traits are clustered. However, correlations among the traits are fairly modest. Each component may
still be viewed as a distinct aspect of socially aversive behaviour.
Cyber aggression: Aggressive, intentional act, using electronic means, to a person or a group of
people irrespective of their age, who perceive(s) such acts as offensive, derogatory, harmful or
unwanted.” encompasses both cyber harassment and cyberbullying, along with other forms of
online aggression
Results
- 35.8% engaged (at least once in the
past three months) in cyber-
aggression
o “Saying things about
someone to make the
person a laughing stock”
was the most used activity
(17.6%).
o Followed by “sending
insulting Facebook
messages or comments to
someone repeatedly”
(15.1%)
- Psychopathy and Facebook intensity significantly predict adolescent’s self-reported cyber-
aggression
o (Those who scored high on psychopathy more often engaged in cyber-aggression)
- Machiavellianism and narcissism were not found to be predictors of cyber aggression
- The 3 personality traits positively correlated
- Intensive Facebook users were associated with higher scores on Machiavellianism and
psychopathy, but not with higher scores on narcissism.
- Boys scored higher on Machiavellianism, psychopathy, and cyber-aggression, whereas girls
tended to be more intensive Facebook users
- Younger adolescents scored significantly higher on psychopathy in comparison to older
adolescents.
, - No support was found for a mediating role of Facebook intensity. Machiavellianism,
narcissism and psychopathy did not significantly predict Facebook Intensity
Implications
As personality traits are fairly stabilised in this age group, cyber-aggression may be used as an
indicator of psychopathy in adolescent individuals.
Prevention: Social perspective-taking skills have been proven successful in overcoming
egocentrism and antisocial behaviour Include training of these skills in prevention
programs
Limitations:
- Short dark triad instrument did not allow to investigate sub-constructs of Machiavellianism,
Narcissism, and Psychopathy
o More recently: Dark Tetrad: Sadism as fourth trait (tendency to derive pleasure for
causing others harm)
- Self-reports: probably underestimation and people were not willing to share online aggressive
behaviour Solution; social desirability scale
- Convenience sample: more girls than boys boys and girls perform different types of
aggression e.g. girls more gossiping and boys are more involved in direct forms of online
aggression.
Using the theory of planned behaviour to understand cyberbullying : the importance of
beliefs for developing interventions ~ Pabian & Vandebosch (2014)
- Proximal determinant: determinants that are directly related to a kind of behaviour
- Distal variable: a variable that is most of the times not directly related to a certain behaviour
e.g. gender.
Research on cyberbullying perpetration has paid relatively little attention to proximal determinants of
this behaviour adolescents (age 11-17)
Proximal determinants: Perceived to influence the behaviour more closely (modifiable by
interventions) can change people’s behaviour more easily than distal determinants as they
are very closely related to the actual behaviour.
o Received few attention in previous research
o Studied in isolation from other proximal determinants.
Research questions:
- Is the Theory of Planned Behaviour (TPB) a good framework for explaining cyberbullying
perpetration?
- Which are the underlying beliefs of the attitude, subjective norm and perceived behavioural
control?
Theory of planned behaviour model ~ Ajzen (1991) (profiling perpetrators)
People’s intention to perform a certain
behaviour is the best predictor of their actual
behaviour. The behavioural intention, in turn,
is determined by three belief-based concepts:
- Attitude: A person’s global affective
evaluation of a behaviour. (more
favourable attitude with regard to
cyberbullying predictor of
cyberbullying behaviour
- The subjective norm / normative
believes: The perception of what
, others think of the behaviour. (when you belief peers approve cyberbullying predictor of
cyberbullying behaviour)
- The perceived behavioural control / risk perception: The perceived ease or difficulty of
performing the behaviour. (Having less concerns about being caught and socially punished)
The more favourable attitude and subjective norm with respect to a behaviour, and the greater the
perceived behavioural control, the stronger should be an individual’s intention to perform the
behaviour under consideration.
Your attitudes/subjective norm etc, are formed based on the beliefs you have e.g. if you
believe that cyberbullying can give you power, your attitude towards cyberbullying can be
positive
Adolescents’ offline and online (risk behaviour)
- Gambling, (un)safe sex, fighting
- Sexting
Prior research ~ Heirman & Walrave (2012): cyberbulling
Shortcoming: only use direct measures, not underlying beliefs of A, SN, PBC.
Focus of this study: adding underlying beliefs
- Attitudes: Why are attitudes positive or negative? Which are the expected positive and
negative outcomes of CB?
- Subjective norm: Which reference groups ultimately generate a positive or negative
influence?
- Perceived behavioural control: What makes CB easy or difficult to perform?
Injunctive norm: assist an individual to determine what is acceptable and unacceptable social
behavior / based on the inference of others' approval
Descriptive subjective norms: Your beliefs if they actually perform the behaviour or not / observation
of others' behaviours
Self-reported cyberbulling
was measures at time 2 (6
months later)
All other items measured at
time 1
To speak of causal
relationships
Results
- In total, 11.7% of respondents reported that they had bullied someone via the internet or
mobile phone in the past six months. (different reference points will lead to different results in
prevalence rates)
- The 3 main factors of the TPB—A, SN and PBC—explain some of the total variance of
adolescents’ intention to cyberbully (28.8%)