1 discussion question (Psychology Expert)

Lee, S.-L. (2019). Predicting SNS addiction with the Big Five and the Dark Triad. Cyberpsychology: Journal of

Psychosocial Research on Cyberspace, 13(1), article 3. http://dx.doi.org/10.5817/CP2019-1-3

Predicting SNS addiction with the Big Five and the Dark Triad

Soon-Li Lee

School of Liberal Arts & Sciences, Faculty of Social Sciences & Leisure Management, Taylor's University Lakeside Campus &

Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Malaysia

Abstract

A considerable amount of literature has widely discussed the issue in regard to the prediction of social networking

sites (SNS) addiction with personality traits. One of the existing issues is the small effect sizes that showed that the

traits outlined by the Five-Factor model are lacking the required specificity to predict specific behaviours such as

SNS addiction. In light of this issue, the present research attempted to predict SNS addiction with the Dark Triad

traits that have been linked to impulsivity that is central to the development of SNS addiction. In this study, a

sample of 204 (Male = 77, 38%; Female = 124, 60%; Not mentioned = 3, 2%; Mage = 22.94, SDage = 3.43) university

students in Malaysia completed the Big Five Inventory, the Short Dark Triad, and the adapted Bergen Facebook

Addiction Scale. Results indicated that SNS addiction was significantly predicted by the measured psychopathy of

the Dark Triad. In predicting SNS addiction, the inclusion of the Dark Triad traits contributed significant amount

of variance after controlling the Five-Factor model. Finally, the implications of the results were discussed in this

manuscript.

Keywords: Social network sites; SNS addiction; the Big Five personality; the Dark Triad

Introduction

Social network sites (SNS) are web-based applications that enable users to construct personal profiles with the

purpose of regulating and maintaining contacts online (boyd & Ellison, 2007). One of the issues of SNS is described

as the failure to regulate SNS usages that lead to negative outcomes (Andreassen & Pallesen, 2014; LaRose, Kim,

& Peng, 2010), commonly known as SNS addiction. Existing research revealed the detrimental effects of SNS

addiction on several domains of functioning that include well-being (Koc & Gulyagci, 2013), interpersonal

relationships (Elphinston & Noller, 2011) as well as self-esteem and life satisfaction (Błachnio, Przepiorka, & Pantic,

2016).

According to Andreassen and Pallesen (2014), personality is an important factor in the development of SNS

addiction. In the literature, research that intends to identify personality traits that are indicative of the risk of SNS

addiction often operationalized personality with the Five-Factor model. The Five-Factor model consists of five

broad domains known as Extraversion that refers to the tendency to seek for companionship from others,

Neuroticism that refers to the tendency to experience negative emotions, Conscientiousness that refers to the

tendency to be organized, Openness to Experience that refers to the tendency to expose oneself to new stimulus

or experience, and Agreeableness that refers to the tendency to be cooperative with others (Benet-Martinez &

John, 1998; John, Donahue, & Kentle, 1991). According to existing research, there are several indicators of the risk

of SNS addiction, which include high Extraversion (Andreassen, Torsheim, Brunborg, & Pallesen, 2012; Wang, Ho,

Chan, & Tse, 2015; Wilson, Fornasier, & White, 2010), high Neuroticism (Caci, Cardaci, Scrima, & Tabacchi, 2017;

Wang et al., 2015), low Conscientiousness (Andreassen et al., 2013; Błachnio & Przepiorka, 2016a; Wilson et al.,

2010), and low Openness to Experience (Andreassen et al., 2013; Błachnio & Przepiorka, 2016a). However, these

traits accounted for a small amount of variance even though the findings supported the significance of these traits

in predicting SNS addiction. For instance, Wilson et al. (2010) found that the broad five domains significantly

predicted addictive tendencies toward SNS with 8.5% of the variance while Błachnio and Przepiorka (2016a) found

that these domains accounted for 6% of the variance. Hence, this illustrates the limited contribution of these traits

in predicting SNS related behaviours (Amichai-Hamburger & Vinitzky, 2010; Ross et al., 2009). Alternatively, the

small amount of variance accounted by the Five-Factor model traits implies that these traits have insufficient

specificity to predict specific behaviours (Hough, 1992; McAdams, 1992). As a result, it is necessary for researchers

to consider other theories of personality to predict the usage of SNS (Ross et al., 2009; Skues, Williams, & Wise,

2012).

It was demonstrated that subclinical personality traits can be indicative of behavioural addiction. Research

suggests that users that are addicted to the internet are more likely to exhibit the characteristics of borderline

personality disorder (Dalbudak, Evren, Aldemir, & Evren, 2014). Similarly, users with high degree of callousness or

lack of empathy are prone to internet addiction (Trumello, Babore, Candelori, Morelli, & Bianchi, 2018). In relation

to SNS usages, the facilitating role of narcissism has been supported by research findings (e.g. Buffardi &

Campbell, 2008). The inclusion of narcissism contributed significantly to the predictive model of SNS usages after

accounting for Extraversion (Ong et al., 2011), indicating that the measured Extraversion did not account entirely

for the measured usages of SNS. In addition, recent findings extend that individuals with elevated

self-centeredness are prone to SNS addiction due to the urge to gratify their needs for affiliation and self-

assurance (Andreassen, Pallesen, & Griffiths, 2017; Casale, Fioravanti, & Rugai, 2016). However, the effect size of

.06 indicates that narcissism is weakly correlated with SNS addiction (Andreassen et al., 2017). Additionally, the

small effect size accounted by narcissism after controlling for Extraversion (Ong et al., 2011) suggests the need to

further explore the role of other related traits in predicting SNS usages. In this case, the present research aims to

explore the relationships of SNS addiction and the three aversive traits of the Dark Triad, namely narcissism,

psychopathy, and Machiavellianism (Paulhus & Williams, 2002). Narcissism is marked by a sense of entitlement,

dominance and a grandiose self-view (Raskin & Terry, 1988). Machiavellianism refers to the tendency to

manipulate others for own gain (Christie & Geis, 1970). Psychopathy consists of the lack of empathy, callousness,

and erratic behaviours (Hare, 2003). These three aversive traits form the Dark Triad that has been linked to several

negative outcomes such as interpersonal difficulties (Stead, Fekken, Kay, & McDermott, 2012), impulsivity (Crysel,

Crosier & Webster, 2013; Jonason & Tost, 2010; Jones & Paulhus, 2011a; Malesza & Ostaszewski, 2016), clinical

psychopathy (Jones & Figueredo, 2013) and sadism (Chabrol, van Leeuwen, Rodgers, & Séjourné, 2009). Apart from

that, recent research on the Dark Triad has associated these traits with online behaviours such as cyber-aggression

(Pabian, De Backer, & Vandebosch, 2015), problematic online gaming (Kircaburun, Jonason, & Griffiths, 2018a),

cyberstalking (Kircaburun, Jonason, & Griffiths, 2018b), cyberbullying (Goodboy & Martin, 2015; Kircaburun et al.,

2018b), and online deception or cybertrolling (Buckels, Trapnell, & Paulhus, 2014; Kircaburun et al., 2018b).

Research extends that certain features on SNS, such as status updates (Garcia & Sikström, 2014) and selfies (Fox

& Rooney, 2015; McCain et al., 2016), appeal to users with salient features of the Dark Triad. Hence, they tend to

exploit these features, which could be a possible cause to their frequent (Fox & Rooney, 2015) and intense use of

SNS (Pabian et al., 2015). It was indicated that frequent use of SNS may escalate into addiction (Hong, Huang, Lin,

& Chiu, 2014) when users are unable to restraint the use of SNS (Błachnio & Przepiorka, 2016b). Recent findings

support the link of the Dark Triad and problematic use of SNS (Kircaburun, Demetrovics, & Tosuntaş, 2018;

Kircaburun et al., 2018b), suggesting that the escalation of prolonged (Fox & Rooney, 2015) and intense use of SNS

(Pabian et al., 2015) into SNS addiction is possible through poor self-control and high degree of impulsivity that

are evident amongst those with salient features of the Dark Triad (Crysel et al., 2013; Jonason & Tost, 2010; Jones

& Paulhus, 2011a; Malesza & Ostaszewski, 2016). Each of the Dark Triad traits significantly correlated with

problematic use of SNS, with psychopathy formed the weakest relationship (Kircaburun, Demetrovics, & Tosuntas,

2018; Kircaburun et al., 2018b). However, psychopathy has been consistently linked to poor self-control and

impulsivity (Jonason & Tost, 2010; Jones & Paulhus, 2011a) that are central to the development of SNS addiction

(Błachnio & Przepiorka, 2016b). Reflecting from this, the present research anticipates the significance of

psychopathy in predicting SNS addiction.

In addition, the purpose of adopting the Dark Triad traits is to address the limited influence of the Five-Factor

model in predicting SNS addiction. It was previously indicated that the Five-Factor model does not reflect

adequately on human personality (Veselka, Schermer, & Vernon, 2011; Veselka, Schermer, & Vernon, 2012).

Consistent with this argument, a research found that the employment of the Dark Triad traits accounted for

additional variance in predicting social values after controlling the Five-Factor model (Kajonius, Persson, & Jonason,

2015). This suggests that the influence exerted by the Dark Triad traits are independent of the Five-Factor model

(Carter, Campbell, & Muncer, 2014).

One of the objectives of the present research is to examine the significance of the Dark Triad traits in predicting

SNS addiction. The present research hypothesizes the significance of psychopathy in predicting SNS addiction

considering that psychopathy is associated with poor self-control and impulsivity (Jonason & Tost, 2010; Jones &

Paulhus, 2011a). The next objective of this research is to compare the variances accounted by the Dark Triad and

the Five-Factor model in the prediction of SNS addiction. Hence, the present research hypothesizes that the Dark

Triad traits will account for additional variance in predicting SNS addiction after controlling the Five-Factor model.

Method

Participants

The sample of the present research consisted of 204 undergraduate students in Malaysia. They were all

Malaysians, aged between 18 and 27 (Mage = 22.94, SDage = 3.43). In the demographic aspect, majority of the

participants were female (Male = 77, 38%; Female = 124, 60%; Not mentioned = 3, 2%), and majority of the

participants were identified as Chinese (Malay = 79, 39%; Chinese = 99, 49%; Indian = 8; 4%; Others = 18, 8%).

Procedure

The present research was advertised at a university’s lecture halls. Those who were interested contacted the

researcher for further arrangement to complete the survey questionnaire. They were invited to complete the

survey questionnaire in a classroom specifically booked for data collection. Informed consents from the

participants were not obtained to ensure anonymity, and no monetary reward was offered to the participants. In

this research, data analysis was conducted using SPSS 19. Ethical clearance was granted by the Monash University

Human Research Ethics Committee.

Measures

Demographics .The demographic details of the participants that include age, gender, and ethnicity were obtained

at the beginning of the questionnaire.

Big Five personality traits. The traits of the Five-Factor model were measured using the Big Five Inventory (BFI;

Benet-Martinez & John, 1998; John et al., 1991). It consists of 44 items that reflect on five dimensions, namely

Openness to Experience (e.g., “I am someone who is curious about many different things”), Conscientiousness

(e.g., “I am someone who is dependable, steady”), Extraversion (e.g., “I am someone who is outgoing, sociable”),

Agreeableness (e.g., “I am someone who is compassionate, has a soft heart”), and Neuroticism (e.g., “I am someone

who is moody, has up and down mood swings”). In the present research, these items were rated on a five-point

Likert scale (1 = Very inaccurate, 5 = Very accurate). Each factor was formed by summing the corresponding items.

The measured five factors exhibited acceptable and high internal consistencies (Extraversion’s α = .71,

Agreeableness’ α = .72, Conscientiousness’ α = .72, Neuroticism’s α = .79, Openness to Experience’s α = .67).

The Dark Triad traits. In the present research, the Dark Triad traits were measured using the Short Dark Triad

(SD3; Jones & Paulhus, 2014). It consists of 27 items that reflect on the three aversive traits, namely psychopathy

(e.g., “I like to get revenge on authorities”), Machiavellianism (e.g., “It’s not wise to tell your secrets”), and narcissism

(e.g., “People see me as a natural leader”). These items were rated on a five-point Likert scale (1 = Strongly disagree,

5 = Strongly agree). Each subscale was formed by summing the corresponding items. The measured traits exhibited

acceptable and high internal consistencies (psychopathy’s α = .75; Machiavellianism’s α = .65; narcissism’s α = .66).

SNS addiction. SNS addiction was measured using the Bergen Facebook Addiction Scale (Andreassen et al., 2012).

In the present research, the items were rephrased to ensure that they are suitable for the SNS contexts. This

measure consists of six items that were rated on a five-point Likert scale (1 = Very rarely, 5 = Very often). A sample

item of this measure is “How often during the last year have you spent more time on SNS than initially intended?”.

The items were summed to form the score for SNS addiction. This measure exhibited high internal consistency

(SNS addiction’s α = .85).

Results

Table 1 summarizes the descriptive statistics and the correlation coefficients. The results indicated that the

correlations ranged from small to moderate, indicating that multicollinearity was not a concern. The VIF values

ranged from 1 – 2.15, with the highest value exhibited by the measured psychopathy. The maximum VIF value of

2.15 does not exceed 10, which further support that multicollinearity was not an issue (Kennedy, 1992). From Table

1, SNS addiction was significantly correlated with psychopathy. The positive correlation suggests that higher

degree of psychopathy increases the risk of SNS addiction. In addition, Neuroticism was positively correlated with

SNS addiction, which indicates that individuals with poor emotional stability are susceptible to SNS addiction.

Agreeableness, Conscientiousness, and Openness to Experience were negatively correlated with SNS addiction.

Table 1. Descriptive Statistics and Correlation Coefficients.

Variables M(SD) 1 2 3 4 5 6 7 8 9

1.Extraversion 24.09(4.42) 1 .08 .10 -.28** .08 .03 -.14* .39** -.05

2.Agreeableness 32.04(4.68) _ 1 .39** -.35** .15* -.54** -.17* -.13 -.18**

3.Conscientiousness 28.23(4.87) _ _ 1 -.39** .14* -.27** -.08 .10 -.19**

4.Neuroticism 24.86(5.03) _ _ _ 1 -.04 .17 .16* -.16* .18*

5.Openness to Experience 34.09(4.53) _ _ _ _ 1 .09 .08 .15* -.14*

6.Psychopathy 21.96(5.45) _ _ _ _ _ 1 .43** .32** .25**

7.Machiavellianism 30.69(5.86) _ _ _ _ _ _ 1 .23** .11

8.Narcissism 25.12(4.75) _ _ _ _ _ _ _ 1 .07

9.SNS addiction 15.18(5.27) _ _ _ _ _ _ _ _ 1

Note: p < .05, **p < .001

Table 2. Hierarchical Regression Predicting SNS Addiction with Demographics and Personality Factors.

First step Second step Third step

Variables β B SE T β B SE t β B SE t

Demographics

Age -.14* -.26* 1.10 -2.37* -.15* -.22* 1.09 -.21* -.14* -.22* .10 -2.03*

Gender -.16* -1.57* 7.76 -2.03* -1.7* -1.88* .78 -.24* -.17* -1.88* .82 -1.63*

Five-Factor Model

Extraversion -.02 -.02 .08 -.26 -.06 -.07 .09 -.78

Agreeableness -.11 -.12 .09 -1.36 .02 .02 .10 .19

Conscientiousness -.06 -.06 .08 -.78 -.05 -.05 .08 -.61

Neuroticism .09 .09 .08 1.10 .09 .09 .08 1.10

Openness to Experience -.16* -.18* .08 -2.26* -.20* -.23* .08 -.277*

Dark Triad

Psychopathy .23** .22** .09 2.25**

Machiavellianism -.03 -.03 .07 -.41

Narcissism .04 .04 .09 .51

F(2, 188) = 4.87*

R2 = .05

Adjusted R2 = .04

F(7, 183) = 3.88**

R2 = .13

R2 change = .08*

Adjusted R2 = .09

F(10, 180) = 3.41**

R2 = .16

R2 change = .03**

Adjusted R2 = .11

Note: *p < .05, **p < .001; a (0 = Male, 1 = Female)

Hierarchical regression with three blocks was conducted. The results of this regression are summarized in Table

2. The first block consisted of the age and gender of the participants, followed by the Five-Factor model, and finally,

the Dark Triad. From Table 2, the initial block accounted for 5% (R2) of the variance. The entry of the Five-Factor

model contributed 8% (R2) of the variance, and the entry of the Dark Triad contributed an additional 3% (R2) of the

variance. The inclusion of the Dark Triad traits significantly contributed to the predictive model, suggesting that

the Five-Factor model did not exhaust the variance in the prediction of SNS addiction. SNS addiction was

significantly predicted by psychopathy, suggesting that greater degree of psychopathy increases vulnerability

towards SNS addiction. Additionally, the Openness to Experience negatively predicted SNS addiction, which

implies that individuals with high openness are less likely to develop SNS addiction. Overall, the predictors involved

in this study accounted for 16% (R2) of the variance.

Discussion

The present research intended to examine the significance and the contribution of the Dark Triad in predicting

SNS addiction. The hypothesized significance of the measured psychopathy as a predictor of SNS addiction was

supported. The secondary psychopathy measured in the present research (see Jones & Paulhus, 2014) has been

linked to risky decision-making (e.g. Dean et al., 2013), poor inhibition and high impulsivity (Jonason & Tost, 2010;

Jones & Paulhus, 2011a; Jones & Paulhus, 2011b; Malesza & Ostaszewski, 2016) that will induce excessive use of

SNS or SNS addiction (Błachnio & Przepiorka, 2016b). Therefore, the findings of the present research suggested

that high degree of secondary psychopathy elevate the risk of SNS addiction. The findings of the present research

indicated that the traits of narcissism and Machiavellianism were not significant predictors of SNS addiction even

though previous research found that frequent (Fox & Rooney, 2015) and intense use of SNS (Pabian et al., 2015)

were significantly correlated to these traits. Hence, this highlighted the importance of psychopathy as the only

significant predictor of SNS addiction due to its conceptual link with impulsivity (Jones & Paulhus, 2011b; Malesza

& Ostaszewski, 2016). The significance of psychopathy contradicted previous findings on the non-significant

relationship of psychopathy and problematic use of SNS (Kircaburun, et al., 2018). The inconsistency can be

explained by the measures used. The Dirty Dozen (Jonason & Webster, 2010) used by previous researchers to

measure the traits of the Dark Triad (Kircaburun et al., 2018) has been criticized for its brevity that leads to

omission of important content (Miller et al., 2012; see also Jones & Paulhus, 2014). Research implicates for caution

when utilizing the Dirty Dozen’s (Jonason & Webster, 2010) psychopathy subscale since it might attenuate

correlations with psychopathic related constructs (Miller et al., 2012). Therefore, it is likely that the relationship of

psychopathy and problematic SNS usage found previously (Kircaburun et al., 2018; Kircaburun et al., 2018b) was

attenuated by the measure used. From a direct comparison, the SD3 (Jones & Paulhus, 2014) used in the present

research demonstrated better validity than the Dirty Dozen (Maples, Lamkin, & Miller, 2014). This suggests that

future research should consider the psychometrics of the measures used to assess the Dark Triad traits.

Narcissism is often linked to self-promotional features on SNS (Fox & Rooney, 2015; Garcia & Sikström, 2014) that

are vaguely represented by SNS addiction (Andreassen & Pallesen, 2014; LaRose et al., 2010). Hence, the link

between narcissism and SNS addiction has been portrayed as weak despite its significance (Andreassen et al.,

2017). The present research found the correlation of .07 that was declared as not significant for narcissism and

SNS addiction, which is slightly larger than the effect size of .06 found by Andreassen et al. (2017). Hence, the large

sample size involved in the respective research may have inflated the link of SNS addiction and narcissism

(Andreassen et al., 2017). Alternatively, the weak correlation of narcissism and SNS addiction can be accounted by

the facets of narcissism. The narcissism subscale of the SD3 (Jones & Paulhus, 2014) used in the present research

reflects on the grandiose sense of self (Maples et al., 2014), which is similar to the Narcissistic Personality

Inventory-16 (NPI-16; Ames, Rose, & Anderson, 2006) used in Andreassen et al.’s (2017) research. Therefore, the

link of grandiose narcissism and SNS addiction has been portrayed as weak. The significant correlation found

previously (Kircaburun et al., 2018; Kircaburun et al., 2018b) was derived from the narcissism subscale of the Dirty

Dozen (Jonason & Webster, 2010) that reflects on both grandiose and vulnerable narcissism (Maples et al., 2014).

Hence, it is likely that problematic SNS usage such as SNS addiction relates better to the vulnerable aspect of

narcissism (Casale et al., 2016). Individuals with high Machiavellianism trait may prefer other forms of social

network or interaction to achieve their goals (Fox & Rooney, 2015). Moreover, individuals with salient features of

Machiavellianism possess greater self-monitoring as an effort to disguise their manipulative tendencies (Abell &

Brewer, 2014). In this light, these individuals are less likely to be impulsive (Jones & Paulhus, 2011a). With the

absence of poor self-control that is central to the development of SNS addiction (Błachnio & Przepiorka, 2016b),

the trait of Machiavellianism did not correlate significantly with SNS addiction.

The present research found that high level of openness predicted lesser risk of SNS addiction, which is akin to

previous findings (e.g. Andreassen et al., 2013; Błachnio & Przepiorka, 2016a). It was also revealed that the trait of

openness to new experience is protective against negative outcomes. Specifically, high degree of openness is

known to reduce the risk of mortality (Ferguson & Bibby, 2012; Jonassaint et al., 2007; Turiano, Sprio, & Mroczek,

2012) as well as the likelihood to develop physical ailment (Israel et al., 2014). Similarly, individuals with high degree

of openness tend to possess higher stress tolerance (Oswald et al., 2006; Williams, Rau, Cribbet, & Gunn, 2009). In

light of these findings, the measured trait of openness may be protective against SNS addiction. Of the five broad

domains, low level of Agreeableness indicates for saliency of the Dark Triad traits (Muris, Merckelbach, Otgaar, &

Meijer, 2017; O'Boyle, Forsyth, Banks, Story, & White, 2015). The present research replicated similar findings,

except for narcissism that was not significantly correlated with Agreeableness. This can be accounted by the weak

link of Agreeableness and narcissism (Muris et al., 2017; O’Boyle et al., 2015). Additionally, the measure utilized to

assess the dark traits might further weakened the relationship between Agreeableness and narcissism. It was

indicated that the effect sizes that reflect on the strength of the relationships of the Five-Factor model and the

Dark Triad traits were larger when the dark traits were measured by the original measures (e.g. Mach-IV, Christie

& Geis, 1970; NPI-16, Ames et al., 2006; Psychopathy Checklist-Revised, Hare, 2003; see Muris et al., 2017).

Therefore, the SD3 (Jones & Paulhus, 2014) utilized in the present research may have attenuated the correlation

coefficients, and thus, further reduce the weak link of narcissism and Agreeableness.

The present results supported that the inclusion of the Dark Triad traits contributed additional variance in the

prediction of SNS addiction after controlling the Five-Factor model. This suggests that the Five-Factor model did

not exhaust the variance in the measured SNS addiction entirely, leaving some additional variance to the Dark

Triad. The present results are consistent with previous research that supported the significance of the Dark Triad

after controlling the broad five domains in predicting perceived male attractiveness (Carter et al., 2014) and social

values (Kajonius et al., 2015). This is an indication that the Five-Factor model does not reflect entirely on human

personality, and the inclusion of the Dark Triad can extend the inadequacy (Veselka et al., 2011; Veselka et al.,

2012). Therefore, the effects exerted by the Dark Triad traits on SNS addiction are independent of the Five-Factor

model. The present findings also supported that the broad five domains of the Five-Factor model are lacking the

required specificity to predict specific behaviours (Hough, 1992; McAdams, 1992) such as SNS addiction.

The findings obtained in the present research further expand the existing literature by focusing on the conceptual

links of the traits measured. In relation to this, the present research revealed that other traits such as psychopathy

of the Dark Triad are also influential even though some of the traits covered by the Five-Factor model have been

significantly associated with SNS addiction. The measured psychopathy was found as the most influential predictor

of SNS addiction due to its conceptual link with impulsivity. Additionally, the importance of the conceptual links of

the measured traits and SNS addiction is further illuminated by the illustrated relationships. Specifically, some

traits may increase vulnerability towards SNS addiction such as psychopathy that predicted SNS addiction

positively, whereas some traits can be protective against SNS addiction as illustrated by the Openness to

Experience that predicted SNS addiction negatively. In this light, it is recommended for future research to consider

the conceptual link and to be more selective with the traits that will be used to predict SNS addiction. Moreover,

the present results have supported that the Five-Factor model has limited influence in predicting SNS addiction

(Amichai-Hamburger & Vinitzky, 2010; Ross et al., 2009). Apart from that, the small effect sizes accounted by the

Five-Factor model supports the recommendation to explore the significance of other personality traits (Ross et al.,

2009; Skues et al., 2012). Therefore, the present findings suggest that further exploration with the Five-Factor

model will only fixate the literature of SNS addiction.

One of the limitations of the present research is its inability to infer for causality due to the correlational design

employed. Moreover, it is important to note that the generalizability of the results is limited due to the diverse and

unequal demographics as well as the small number of student sample. In addition, the small effect sizes from the

hierarchical regression show the need to expand the investigation on the conceptual link of SNS addiction with

other personality traits. The use of concise measures of the Dark Triad, such as the SD3 (Jones & Paulhus, 2014),

affect the results by attenuating the effect sizes. Hence, future research should measure the traits of the Dark

Triad with the original measures. Due to the conciseness of the SD3 (Jones & Paulhus, 2014), the present research

could only measure a fragment of the Dark Triad traits while these traits may be multifaceted (see Furnham,

Richards, & Paulhus, 2013). Thus, it is also imperative for future research to assess the role of different facets of

the Dark Triad traits (e.g. primary psychopathy, secondary psychopathy) in shaping SNS addiction.

In summary, the present research concludes that the measured psychopathy of the Dark Triad is the most

influential predictor of SNS addiction. It is also concluded that the Dark Triad traits accounted for more specificity

compared to the Five-Factor model in the prediction of SNS addiction. Therefore, this further supports the

recommendation of exploring traits other than the Five-Factor model.

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Faculty of Social Studies, Masaryk University | Contact | Editor: David Smahel

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Correspondence to:

Soon Li Lee

School of Liberal Arts & Sciences, Faculty of Social Sciences & Leisure Management

Taylor's University Lakeside Campus

Jalan Taylors 1

Subang Jaya 47500

Malaysia

Email: soonli.lee(at)taylors.edu.my

Editorial record: First submission received on April 26, 2018. Revisions received October 16,2018, and November 27,

2018. Accepted for publication on January 2, 2019.

About Author

Dr. Lee Soon Li (Ph.D. Monash University Malaysia, 2017) is a lecturer at Taylor’s University Lakeside Campus. His

research areas include the effects of media use on psychological well-being, the influence of personality on media

use, and psychometrics.

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