Personality Traits as Predictors of Social Networks ...

Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(3): 182- 195 © Scholarlink Research Institute Journals, 2015 (ISSN: 2141-7016) jeteas.scholarlinkresearch.com Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(3):182- 195 (ISSN: 2141-7016)

Personality Traits as Predictors of Social Networks Addiction among University Students 1

Ahmad A. Rabaa’i, 2BasharZogheib and 2Enas AlJamal

1

Department of Computer Science and Information Systems, College of Arts and Sciences, American University of Kuwait (AUK), Safat, Kuwait 2 Department of Mathematics and Natural Sciences, College of Arts and Sciences, American University of Kuwait (AUK), Safat, Kuwait Corresponding Author: Ahmad A. Rabaa’i _________________________________________________________________________________________ Abstract Social network platforms (SNPs) are online sites that enable users to create public profiles, interact with real-life friends, and meet other people based on common interests and beliefs. Given their social-oriented characteristics, SNPs provide their users with an enjoyable interaction experiences. However, these experiences may encourage users to uses these platforms extensively and hence results in addictive use behaviors. By incorporating both, psychological and technological perspectives, this study aimed at examining the relationship between personality traits and social network platforms (SNPs) addiction. While a number of other studies have highlighted the danger that excessive SNPs may pose to university students as a population group, to the best of our knowledge, this is the first study that discusses this issue in the Gulf Cooperation Council (GCC) region. Data was collected from 434 students at a private American University in the Stat of Kuwait. Four out of the five- factor model of personality, including: Neuroticism, Extroversion, Openness to experience, and Agreeableness show significant association with SNPs addiction, while the Conscientiousness factor was not significant. Partial Least Squares (PLS) of Structured Equation Modelling (SEM) analysis demonstrates that 53% of the variance of SNPs addiction was explained by the five-factor model of personality. Results of this study may benefit universities in dealing with students who suffer from this kind of addiction. The research limitations and implications are discussed. __________________________________________________________________________________________ Keywords: addiction, personality traits, big five, social network platforms, snp, kuwait by the people they communicate with online. In fact, the maintenance of already established offline networks itself can be seen as an attraction factor, which according to Sussman et al. (2011) is related to the etiology of specific addictions. For instance, In many areas of behavioral addiction, a number of addictive behaviors (e.g., alcoholism, video game addiction) may be maintained and hard to break because of the social ties that the addict has with others that engage in the activity (Griffiths, 1996), and this holds true for addiction to SNPs.

INTRODUCTION Social Network Platforms (SNPs) such as Twitter, Instagram, Facebook, or LinkedIn, have shown dramatic growth over the last decade. For instance, SNPs are increasingly enmeshed in contemporary society (Chui et al. 2012), this rapidly evolving phenomenon transforming ways of interacting, working, creating value, knowledge acquisition and innovation (Urquhart and Vaast 2012). Haenlein (2010, p. 61) defined SNPs as a “group of internet based applications that build on the ideological and technological foundation of web 2.0 and allow creation and exchange of user created contents”.

Factors related to SNPs addiction have been investigated from sociological (i.e. age, race, and gender) and psychological perspectives. This study focuses on the psychological aspects of SNPs addiction; more specifically, the influence of user’s personality on SNPs addiction. Personality refers to the all aspects of a person’s individuality. Personality is a significant factor that may contribute to both chemical and behavioral addictions is personality (Grant et al., 2010). One of the most influential personality theories is the five-factor model of personality which differentiates between five main

Recent evidence suggests that individuals may feel compelled to maintain their online social networks in a way that may, in some circumstances, lead to using SNPs excessively (Griffiths et al., 2014). SNPs are usually used in order to maintain offline relationships or support the establishment of offline relationships (Amichai-Hamburger &Vinitzky, 2010). According to Kaplan and Haenlein (2012), the more time an individual spends on the Internet, the greater is the social behavioural influence exerted on the individual 182

Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(3):182- 195 (ISSN: 2141-7016) dimensions: (1) Neuroticism (e.g., being nervous and anxiety prone), (2) Extroversion (e.g., being talkative and outgoing), (3) Openness to experience (being imaginative and intellectually oriented), (4) Agreeableness (e.g., being sympathetic and warm) and (5) Conscientiousness (e.g., being organized and prompt) (Wiggins, 1996; John et al, 2008). The study also recognizes the technological aspects of SNPs addiction and usesa short version of the Charlton andDanforth (2007) addiction scale.

personality traits; and (c) an abbreviated research on past studies of social networks addiction; Section 3 discusses the research model and hypotheses development; Section 4 explains the research method; Section 5 presents the research findings and the hypotheses testing; followed by the research conclusions, limitations and future research in Section 6. LITERATURE REVIEW Social Network Platforms By emphasizing people‘s behaviours when engaged in social networks, Dykeman (2008, p. 1) defined SNPs as: “the means for any person to: publish digital, creative content; provide and obtain realtime feedback via online discussions, commentary and evaluations; and incorporate changes or corrections to the original content”. It has become clear that SNPs have overtaken personal email, and become the fourth most popular Internet activities, following search, portals, and PC software applications (Nielsen, 2009). Nail (2009) reported that 75% of online users are currently SNPsusers. Waters et al (2009) suggested that, rather than replacing face-to-face communication or interaction, SNPsprovide new opportunities to develop relationships and enhances one‘s social connections with others through sharing of. Boyd and Ellison (2007) characterize SNPsas web-based services that allow individuals to: (1) construct a web presence usually including a photo and descriptors like location, age, study concentration and interests, (2) publicly display a list of other users with whom they share a connection, and (3) to traverse those list of connections to view the profiles of others within the system.

Despite the increasing importance of SNPs, researchinto their addiction in relation to personality traits remains in its early stages. Nonetheless, there is some evidence of that differences in individuals’ personalitytraits determine their online behaviours (McCrae & Costa, 2004). In relation to addiction to social networking, one study found that excessive social networks use was positively associated with Extroversion and negatively associated with Conscientiousness (Wilson et al., 2010). However, a recent study of Facebook addiction found it to be positively related to Neuroticism and Extroversion, and negatively related to Conscientiousness (Andreassenet al., 2012). Various research addressing the psychologically addictive characteristics of SNPs have led to a growing concern amongst educators about the influence of SNPs on children’s and adolescents’ well-being (Akhavi et al., 2013) and anumber of other studies have highlighted the danger that excessive SNPs may pose to university students asa population group (e.g. Tsai et al., 2009; Wan, 2009; Kuss, & Griffiths, 2011;Sofiah et al., 2011; Alabi, 2012; Akhavi et al., 2013). According to a study conducted by Marketing Türkiye (2012), 9 out of 10 young people are members of social media forums and spend half of their spare time (equivalent to between 4 and 6 hours per day) on social networking websites. Additionally, the youth population (67% of the entire population aged under 35years old) of the Gulf Cooperation Council (GCC) region will result in faster adoption and higher usage of SNPs in the coming years (Markaz, 2014).

Chui (2012) classifies these different applications as: Blogs, Microblogs, Media sharing, Wikis, Social Network Sites, Social commerce, Social gaming, Shared work space, Q&A websites, Forum and Review websites. Each of these application groups has their own functionalities which make them appropriate for particular uses. Chan-Olmsted et al (2013) arguethat the usage pattern of Internet surfers has shifted from that of passive readings to active building of contents, illustrating the user-centric, interactive, and collaborative nature of Web 2.0. Among all platforms enabled by the advancement of Web 2.0, social networks are the most significant application that has grown exponentially in many population segments (Chan-Olmsted et al, 2013). In the GCC region, Kuwait Financial Centre “Markaz” recently published a report on GCC SNPs. In this report, Markaz examines the trends in usage and penetration of Facebook, LinkedIn and Twitter in the GCC countries. The report highlights the growth drivers, opportunities and key challenges for the sector. Among GCC countries, Saudi Arabia

The objective of this paper is aimed at examining the relationship between personality traits and SNPs addiction. The study was conducted in Kuwait; despite the ever-growing popularity of the Internet and SNPs as well as the presence of substantial body of research on social networks, to the best of our knowledge, this is the first study that investigates the relationship between personality traits and SNPs addiction in Kuwait and in the GCC region in general. The paper is structured as follows. Following the Introduction, Section 2 provides (a) an overview of social network platforms,(b) an overview of 183

Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(3):182- 195 (ISSN: 2141-7016) and UAE are the frontrunners in SNPs adoption. Currently, Facebook is the most widely used SNP tool in the GCC, with over 16 million users (Apr 2014) in the region. Twitter and LinkedIn also have significant user base in GCC, with around 3 million users for each of platform (Markaz, 2014).Kuwait has the highest percentage of SNPs users, in proportionate to the population, in the Middle East(Maarefi, 2013), leading the world in Twitter, with 1 in every 3 Kuwaitis has an active account. While Facebook penetration takes a dive in Kuwait, with only 29.53% of the population have an active account, Kuwait is most active country in the Arab region on Instagram (Kuwaitiful, 2013).

advice (Openness)? (iv) Who will be a good cooperator and reciprocator Agreeableness)? And (v) Who will work industriously and dependably (Conscientiousness)?

Personality has drawn interest of many researchers in different contexts. For example, in academic achievement (Komarraju et al., 2011), in consumer behavior (Kassarjian, 1971),job performance (Barrick& Mount, 1991), media preferences (Kraaykampa and van Eijck (2005), in Internet banking (Grabner-Kräuter&Faullant,2008), and in technology adoption (Vishwanath, 2005).

Abbreviated Research on Past Studies of Social Networks Addiction Wan (2009) examined SNPs addiction in a sample of 335 Chinese college students aged between 19 and 28 years using the Internet Addiction Test of Young (1998). Respondents were considered addicted when they certified five or more of the eight IAT items. The author assessed loneliness, user gratifications, usage attributes, and patterns of SNPs use. The results indicated that 34% were classified as addicted.Olowu and Seri (2012) studied social networking behaviour among 884 Nigerian university students. Results indicated that 304 participants (34%) claimed to use social networks very often. The majority (64%) strongly agreed that they had an inability to stop using social network sites, and 25% said they “very often” overspent time on SNPs. A significant minority (21%) said they were very often agitated if unable to use social networks, and a slightly larger number (27%) strongly agreed that they were addicted to social networking. Additionally, Machold et al. (2012) investigated general patterns of Internet usage among 474 young Irish teenagers (aged 11–16 years) and also attempted to identify potential online hazards, including overuse and addiction. 72% the sample reported frequent social networking, with most of these being Facebook users (95%), while 33% of the sample felt they engaged in social networking too often.

Psychology researchers have developed a framework called the Big Five-Factor Model (McCrae & Costa, 1997; John &Srivastava, 1999), which structures most of the current studies of personality (Correa et al., 2013).Gosling et al. (2003) argued that the BigFive framework is a hierarchical model of personality traits with five broad factors, which represent personality at the broadest level of abstraction. Each bipolar factor (e.g., Extraversion vs. Introversion) summarizes several more specific facets (e.g., Sociability), which, in turn, subsume a large number of even more specific traits (e.g., talkative, outgoing).Correa et al., (2013) state that most individual differences in human personality can be classified into five broad, empirically derived domains: extraversion, neuroticism, openness to new experiences, agreeableness, and conscientiousness. Buss (1991) argued that the five-factor model reflects individual differences which are strongly related to solving social adaptive problems in an evolutionary context. For example, according to Andreassen et al. (2013): (i) Who will burden me with their problems and fail to cope well with adversity (Neuroticism)? (ii) Who will gain high status in the social hierarchy (Extroversion)? (iii) Who are able to provide good

Cam and Isbulan (2012) studied gender differences in Facebook addiction in 1,257 Turkish university students (739 females and 518 males; aged 20–24 years). The authors adapted Young’s (1998) Internet Addiction Test and named the new instrument the Facebook Addiction Scale (FAS). The reliability of the scale was calculated with a very highCronbach’s alpha (0.92). Results showed males scored significantly higher than females on the FAS. Also, Alabi (2012) examined Facebook addiction among 1,000 Nigerian University undergraduates using stratified and purposive sampling. The study used an instrument devised by the authors, the Facebook Addiction Symptoms Scale (FASS) with good internal consistency and a Cronbach’s Alpha of 0.73. Respondents answer the statements on a four-point Likert scale from 1 (Not at all) to 4 (Very regular). The FASS contains three items each under the following five categories: (1) preference for social network site, (2) loss of control, (3) preoccupation, (4) negative life consequences, and (5) withdrawal. Results showed that 31% of the sample accessed their Facebook account every hour. The study also revealed a relatively low level of Facebook addiction (1.6%). However, Alabi suggested that the low level

Personality Traits Scientifically, personality is “conceptualized as the entire mental organization of a person’s traits, where traits are defined as a cross-situational and temporally stable set of individual attributes” (Wehrli, 2008). For instance, personality is a stable psychological feature that is related to a broad range of behaviors and attitudes (Correa et al., 2013).

184

Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(3):182- 195 (ISSN: 2141-7016) of Internet access generally in Nigeria may have had an impact on the results.

euphoria, loss of control, withdrawal, and relapse/reinstatement). Results indicated that time spent on Facebook varied between 10 minutes and 70 hours a week with a mean of 7 hours a week. Regression analysis of the data demonstrated that only 22% of the variance in Facebook addiction was explained by four significant predictors (i.e., weekly time commitment, social motives, anxiety and insomnia, and severe depression), and all were positively associated with addictive usage.

Wilson et al. (2010) surveyed 201 students in an Australian university (76% female, mean age = 19 years) to assess personality factors via the short version of the NEO Personality Inventory, time spent using SNPs, and an Addictive Tendencies Scale. The Addictive Tendencies Scale included three items measuring salience, loss of control, and withdrawal. The results of a multiple regression analysis indicated that high extraversion and low conscientiousness scores significantly predicted both addictive tendencies and the time spent using an SNPs. The researchers suggested that the relationship between extraversion and addictive tendencies could be explained by the fact that using SNPs satisfies the extraverts’ need to socialize. Andraessen et al. (2012) constructed the Bergen Facebook Addiction Scale (BFAS) based on Griffiths’ (2005) six addiction components. Their study surveyed 423 students together with several other standardized self-report scales (e.g., including measures that assessed personality, attitudes toward Facebook, the Addictive Tendencies Scale). Findings show positive relation to various personality traits (e.g., neuroticism, extraversion), and negatively related to others (e.g., conscientiousness). High scores on the new scale were also associated with going to bed very late and getting up very late. Findings of this study made the authors suggest that the respondent is addicted to Facebook.

However, Griffiths (2012) noted that, for many researchers, Facebook addiction has become almost synonymous with SNPs addiction. However, Facebook is just one of many websites where social networking can take place. general public (e.g. Facebook); others are more focused (e.g. LinkedIn focused on professional networks). Some emphasize media sharing (e.g. Youtube, Flickr), while others, such as weblogs, are popular because they are easy to create and maintain (Kietzmann et al. 2011). In fact, Griffiths (2012) argued that most of the scales that have been developed have specifically examined excessive Facebook use such as the Bergen Facebook Addiction Scale (Andreassen et al., 2012), the Facebook Addiction Scale (Cam and Isbulan, 2012), and the Facebook Intrusion Questionnaire (Elphinston and Noller, 2011). Additionally, most of prior studies on SNPs addiction suffer from either methodological issues or the sample is too small for generalization to be established. Also, Griffiths et al. (2014) suggested that Empirical studies need to ensure that they are assessing addiction rather than excessive use and/or preoccupation.For instance, SNPs are diverse, varying in scope and functionality (Emamjome et al., 2014). Some target the

Koc and Gulyagci (2013) examined Facebook addiction among 447Turkish college students and assessed the associated behavioral, demographic,and psychological health predictors. The authors developed a Facebook Addiction Scale (FAS) to assess addictive Facebook usage comprising. The FAS consists of eight items relatedto the core components of addiction (e.g., cognitive and behavioral salience,conflict with other activities,

THE RESEARCH MODEL AND HYPOTHESES DEVELOPMENT The Research model of this study is shown in Figure 1.

Figure 1: The Research Model and its possible association with behavior on social network sites. The following is a summary on Wehrli’s discussion:

In his research, titled “Personality on Social Network Sites: An Application of the Five Factor Model”, Wehrli (2008, p 5-6) discusses each personality trait 185

Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(3):182- 195 (ISSN: 2141-7016) Conscientiousness refers to the extent that an individual is dependable, careful, responsible, organized, and has a high will to achieve. It has been shown to be associated with performance in the workplace and is known to be the most prominent dimension in the context of education and learning, exhibiting substantial correlations with grade point average, educational performance and persistence. Furthermore, one might expect this trait to be the central source of strategic network formation. However, Wehrli state that high scores on Conscientiousness will lead to lower numbers of contacts in this specific context. Conscientious individuals will refrain from high investments in SNPs profiles; they will stick to their main goals and try to avoid such sources of distraction.Also, Wilson et al. (2010) indicated that low conscientiousness scores significantly predicted both addictive tendencies and the time spent using SNPs. This finding appears to be in line with previous research on the frequency of general Internet use in that people who score low on conscientiousness tend to use the Internet more frequently than those who score high on this personality trait (Landers &Lounsbury, 2004).As such, the study makes the following hypothesis H1: Conscientiousness people will show no addiction to SNPs

curiosity, originality and open-mindedness. Low openness scores indicate people who are practical, traditional and down-to-earth. In the context of SNPs it is expected that individuals with high scores on openness to be more likely to try, to use and to keep up with new social networking platforms. For instance, high openness to experience is reflected in curiosity and novelty-seeking; low levels are evident in preferences for adhering to convention and established patterns (John &Srivastava, 1999). Mark and Ganzach (2014) argued that Openness should be positively related to general Internet use.Evidence also suggests people who are open to new experiences are heavier users of SNPs (Guadagno et al., 2008; Ross et al., 2009). Therefore, the study makes the following hypothesis: H3: Openness to experience people may show more addiction to SNPs. Extraversion refers to the extent to which individuals are outgoing, active, assertive and talkative. Extraverts are expected to approach others more easily and engage in more social interaction. In contrast, individuals with low levels of extraversion tend to be “introverted,” reserved, serious, and prefer to be alone or stay within close circles. Asendorf and Wilpers (1998) found that extraversion was highly associated with students’ interaction rates and their peer-relationship formation. Extraversion is the least controversial dimension in this context and is expected to exhibit obvious and strong effects. Additionally, extraverted people had many connections with others via social networking platforms and in the ‘‘real world” (Zywica&Danowski, 2008). Mark and Ganzach (2014) argued that extroversion should be positively related to general Internet use. Further, Quercia et al. (2011) found that extraversion was positively related to Twitter usage. Also, Ross et al. (2009) found extraversion was positively related to belonging to Facebook groups, but there was no association with how they communicated on the site. They argued that the lack of instant messaging available to Facebook users may not have fulfilled their desire for immediate contact. Facebook has since introduced an instant messaging application, which suggests that extraversion may now be positively correlated with SNPs addiction. Also, in their study, Wilson et al. (2010) indicated that high extraversion scores significantly predicted both addictive tendencies and the time spent using SNPs. The researchers suggested that the relationship between extraversion and addictive tendencies could be explained by the fact that using SNPs satisfies the extraverts’ need to socialize. Hence, the study makes the following hypothesis: H4: Extraverted people may show more addiction to SNPs. Agreeableness. Agreeable persons tend to be courteous, kind, flexible, trusting, forgiving, are inclined to cooperate but known to avoid conflict.

Neuroticism refers to the extent to which individuals experience and display negative affects like anxiety, sadness, embarrassment, depression, guilt, and is tied to the ability to cope with stress. Individuals with high levels on the factor neuroticism are expected to impose higher tie maintenance costs on their alters, although these negative consequences are less plausible in a computer-mediated environment with a very low tie formation threshold and, on average, low tie strength. On the other hand, people with high scores on neuroticism tend to believe that they are not attractive to others and are fearful of rejection. Therefore an intensified desire for an unstained selfpresentation could result –counter-intuitively – in higher activities on SNPs. Mark and Ganzach (2014) argued that neuroticism should be positively related to general Internet use.Moreover, Ehrenberg et al., (2008) argue that people high in neuroticism had greater instant messaging use. The authors speculate this preference over face-to-face interaction was because the instant messaging permitted additional time to contemplate responses, making it easier for more neurotic people to communicate with others. Therefore, the study makes the following hypothesis: H2: Neuroticism people may show more addiction to SNPs Openness. Wehrli suggested that openness to experience may have the strongest influence on social and interpersonal phenomena among all of the five factors. The Openness dimension measures the propensity of individuals to display imagination, 186

Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(3):182- 195 (ISSN: 2141-7016) 302 used Twitter (TW). It also shows that 136 respondents had used both platforms.

Agreeableness is associated with positive relations to alters, and has been shown to foster peer acceptance and friendship. McCarty and Green (2005) report that agreeableness and conscientiousness were most highly correlated with personal network structure, while they found a small influence from extraversion. Generally, agreeableness is said to have favourable influence to social interactions and their perceived quality. Based on this, the study makes the following hypothesis: H5: Agreeableness people may show more addiction to SNPs.

Table 2: FB vs. TW Cross-tabulation FB Total

Table 3: FB vs. Insta Cross-tabulation Insta. Total 23 212 235 FB 32 167 199 Total 55 379 434 The personality traits were assessed using part of the 10-ItemPersonality Inventory developed by Gosling et al. (2003). This scale was devised as a brief measure of the Big-Five dimensions of personality. The 10-Item Personality Inventory has adequate levels of validity, reliability and external correlation (Gosling et al., 2003). Gosling et al. (2003) argue that it can be used as a proxy for the longer Big-Five instruments (Gosling et al., 2003). A snapshot of the Personality trait scale used in the instrument in presented in Figure 2.

Table 1: Demographic data of the respondents Frequency

Personality Traits The following are a number of personality traits that may or may not apply to you. Please write a number next to each statement to indicate the extent to which you agree or disagree with that statement. You should rate the extent to which the pair of traits applies to you, even if one characteristic applies more strongly than the other.

Percentage

187 247 434

43.1 56.9 100.0

23 373 25 13 434

5.3 85.9 5.8 3.0 100.0

Total 235 199 434

Table 3 shows that the number of respondents who used Facebook (FB) was 199 and 379 used Instagram (Insta.). It also shows that 167 respondents had used both platforms.

THE RESEARCH METHOD Sample The sample comprised 434 undergraduate studentsat the American University of Kuwait – The State of Kuwait. Of the 434 valid responses, 247 were females (56.9%) and187 males (43.1%). Only 5.3 percent of the respondentsare aged less than 18 years; 85.9 percent were aged between 18-25, 5.8 percent were age between 26-30 years; and only 3.0 percent were above 40 years of age. Additionally, the majority of the respondents 37.6 percent were in their first year of studies, while only 15.7 percent were in their fourth year. Also, the vast majority of the respondents 84.8 percent were Middle Eastern, while only 1.4 percent were from Australia, Europe, North America and South America. Table 1 shows a snapshot of the respondents’ demographic data.

Data Gender Male Female Total Age Less than 18 years 18 – 25 years 26 – 30 years More than 30 years Total Year of Study First year Second year Third year Fourth year Total Ethnicity Africa Asia Australian Europe Middle East North America South America Total

TW 166 136 302

69 63 132

Disagree strongly

Disagree moderately

Disagree a little

1

2

3

Neither agree nor disagree 4

Agree a little

Agree moderately

Agree Strongly

6

7

5

1

163 125 78 68 434

37.6 28.8 18.0 15.7 100.0

16 44 1 2 368 2 1 434

3.7 10.1 0.2 0.5 84.8 0.5 0.2 100

I see myself as : 1. ___ Extraverted, enthusiastic. 2. ___ Critical, quarrelsome. 3. ___ Dependable, self-disciplined. 4. ___ Anxious, easily upset. 5. ___ Open to new experiences, complex. 6. ___ Reserved, quiet. 7. ___ Sympathetic, warm. 8. ___ Disorganized, careless. 9. ___ Calm, emotionally stable. 10. ___ Conventional, uncreative.

Figure 2: The Personality Trait Scale used in this Study To capture addiction with SNPs, a short version of the Charlton and Danforth (2007) scale was used. The selected items have a loading of more than 0.7 in the original study. Also, the selected items capture the prevalence of typical behavioral addiction

SURVEY INSTRUMENT Respondents were asked to reflect on their experience with their most frequently used SNPs.In terms on the used SNPs, Table 2 shows that the number of respondents who used Facebook (FB) was 199 and

1

187

(‘”R” denotes reverse-scored items): Extraversion: 1, 6R; Agreeableness: 2R, 7; Conscientiousness; 3, 8R; Emotional Stability: 4R, 9; Openness to Experiences: 5, 10R.

Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(3):182- 195 (ISSN: 2141-7016) symptoms consistent with Brown’s (1997) conceptualization, which is commonly applied for measuring technology-related addictions (Byun et al, 2009). For example, items Add2 and Add3 capture symptomatic conflict, and item Add5 captures relapse and reinstatement symptoms (Ture&Serenko, 2012). Moreover, the selected items can pertain to any IT, beyond the original context of online games. Further,

these items were used in Ture and Serenko (2012) of social media addiction and have shown adequate levels of validity, reliability and external correlation. A seven point Likert scale with anchors of strongly disagree to strongly agree was used to measure each item. A snapshot of the Addiction scale used in the instrument in presented in Figure 3.

For each question, please select the most appropriate answer: Strongly disagree 1

2

3

4

5

6

Strongly Agree 7

ADD1 I sometimes neglect important things because of my interest in social networks platforms. ADD2 My social life has sometimes suffered because of me interacting with social networks platforms. ADD3 Using social networks platforms sometimes interfered with other activities. ADD4 When I am not using social networks platforms, I often feel agitated. ADD5 I have made unsuccessful attempts to reduce the time I interact with social networks platforms.

Finally, respondents were asked to answer the following two (yes or no) questions; In your opinion, do you over-use social network platforms? And, in your opinion, do you feel that you are addicted to social network platforms? 78% think that they overuse SNPs, while 22% do not. Admittedly, 68% believe that they are addicted to SNPs, while only 32% do not think the same.

model and (2) assessing the inner (path) model. The reliability and validity of the outer-model need to be established before the inner-model is examined (Henseler et al., 2009). THE MEASUREMENT MODEL Tests for internal consistency, items’ loadings, convergent validity and discriminant validity were conducted. Internal consistency reliability and indicators reliability were also evaluated. Specifically, Cronbach’s Alpha (Cronbach, 1951), Composite Reliability (Werts et al., 1974) and examination of item loadings (Carmines & Zeller, 1979) cross-loadings (e.g. Yoo & Alavi, 2001) and average variances extracted (AVE) (Fornell&Larcker, 1981) were used. The results are shown in Table 4.

FINDINGS Partial Least Square (PLS) of structure equation modelling (SEM) was used to analyze the data of this study. The research model presented in Figure 1 was analyzed using SmartPLS 3.0 (Ringle, Wende, & Will, 2014).Validation of PLS models involve a twostep process: 1) assessing the outer (measurement)

Table 4:Items loading, Cronbach’s alpha, Composite reliability and AVE Items CON 1 CON 2

Loading

Cronbach’s Alpha

Composite Reliability (internal consistency reliability)

AVE

0.8347

0.9120

0.8884

0.8845

0.9254

0.9049

0.9127

0.9329

0.9271

0.9013

0.9584

0.9451

0.8763

0.9024

0.9328

0.9677

0.9443

0.8874 0.8742 Conscientiousness

NEO 1 NEO 2

0.8984 0.9140 Neuroticism

EXT 1 EXT 2

0.9027 0.9255 Extroversion

AGR 1 AGR 2

0.8759 0.9028 Agreeableness

OPE 1 OPE 2

0.9048 0.9227 Openness to experience

ADD 1 ADD 2 ADD 3 ADD 4 ADD 5

0.9129 0.9328 0.9552 0.9544 0.9241 Addiction

0.9247

square roots of the AVEs, are greater in all cases than the off-diagonal elements in their corresponding row and column, supporting the discriminant validity of the item scales.

Table 5 provides evidence of the discriminant validity of the item scales used in this study. The bolded items in the matrix diagonals, representing the 188

Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(3):182- 195 (ISSN: 2141-7016) Table 5:Discriminant validity (inter-correlations) of the item scales Conscientio-usness Neuroticism Extroversion Agreeablen-ess Openness to experience Addiction

Conscientiousness

Neuroticism

Extroversion

Agreeableness

0.9426 0.5448 0.1128 0.3690 0.1943 0.2146

0.9513 0.2194 0.3251 0.3222 0.2143

0.9629 0.2009 0.2154 0.2216

0.9722 0.1187 0.1054

The convergent validity of the item scales were assessed by extracting the factor loadings (and cross loadings) of all items to their respective construct. These results, shown in Table 6, indicate that all items loaded: (1) on their respective construct from a lower bound of 0.8742 to an upper bound of 0.9552and (2) more highly on their respective

Openness to experience

Addiction

0.9658 0.0984

construct than on any other construct (the non-bolded factor loadings). A common rule of thumb to indicate convergent validity is that all items should load greater than 0.7 on their own construct, and should load more highly on their respective construct than on the other constructs (e.g. Yoo & Alavi, 2001).

Table 6: Factor loadings (bolded) and cross loadings Openness Addiction to experience CON 1 0.2219 0.2849 0.3157 0.1746 0.2354 0.8874 CON 2 0.2341 0.3214 0.3471 0.1842 0.2641 0.8742 NEO 1 0.3251 0.2114 0.2214 0.5418 0.2317 0.8984 NEO 2 0.3331 0.1889 0.1984 0.3541 0.2445 0.9140 EXT 1 0.1948 0.1540 0.2001 0.2214 0.2361 0.9027 EXT 2 0.1884 0.1624 0.2147 0.3257 0.2239 0.9255 AGR 1 0.1749 0.8842 0.1452 0.2334 0.2549 0.8759 AGR 2 0.1654 0.0941 0.1136 0.2143 0.2455 0.9028 OPE 1 0.3254 0.1521 0.1134 0.2284 0.2778 0.9048 OPE 2 0.3364 0.2214 0.2341 0.2140 0.2659 0.9227 ADD 1 0.2581 0.2154 0.2350 0.3321 0.2224 0.9129 ADD 2 0.2349 0.2021 0.2014 0.3219 0.1984 0.9328 ADD 3 0.2203 0.2214 0.2269 0.3641 0.1148 0.9552 ADD 4 0.2654 0.2335 0.2251 0.3336 0.0954 0.9544 ADD 5 0.2558 0.2411 0.2311 0.3417 0.3288 0.9241 2009, p: 304). Path coefficients should exceed .100 to account for a certain impact within the structural The Structural Model Based on the suggestions of Chin (1998), the model (Urbach & Ahlemann, 2010). Furthermore, assessment of the structural model entails: Estimates path coefficients should be significant at least at the for path coefficients (β) and Determination of .050 level (Henseler, et al., 2009; Urbach & coefficient (R2). Ahlemann, 2010). Items

Conscientiousness

Neuroticism

Extroversion

The first step in assessing the structural model, using PLS, should be based on the path coefficient’s ( ) direction algebraic sign, magnitude and significance (Chin, 1998, 2010; Götz, et al., 2010). In PLS, the individual path coefficients of the structural model can be interpreted as standardised beta coefficients of ordinary least squares regressions (Henseler, et al.,

Agreeableness

Figure 3 shows the structural model results omitting the influence of the interacting moderator variables. All, except one, beta path coefficients ( ) are positive (i.e. in the expected direction) and statistically significant (at p < 0.05).

189

0.9718

Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(3):182- 195 (ISSN: 2141-7016)

Figure3: The Addiction Scale used in this Study social networks by exploring the relationship between personality traits of the five-factor model and SNPs addiction.

Additionally, since the main purpose of the structural model is to assess the relationships between hypothetical constructs (Götz, et al., 2010), the most essential criterion for the assessment of the structural model is the coefficient of determination (R2) of each of the constructs in the model. R2 values should be sufficiently high for the model to have a minimum level of explanatory power (Chin, 1998, 2010; Götz, et al., 2010; Henseler, et al., 2009; Urbach & Ahlemann, 2010). In PLS, R2 values represent “the amount of variance in the construct in question that is explained by the model”(Chin, 2010, p: 674). Chin (1998) considers R2 values of approximately 0.67, 0.33, and 0.19 as substantial, moderate and weak respectively. The R2values of this study are shown in Figure 3.

Also, while a number of studies have highlighted the danger that excessive SNPs may pose to university students as a population group, to the best of our knowledge; this is the first study that discusses this issue in the Gulf Cooperation Council (GCC) region. Data was collected from 434 students at the American University of Kuwait. PLS analysis of the study data shows that 53% of the sample suffers from SNPs addiction. The study results demonstrated that four out of the five- factor model of personality, including: Neuroticism, Extroversion, Openness to experience, and Agreeableness show significant association with SNPs addiction, while the Conscientiousness factor was not significant.

SUMMARY OF THE HYPOTHESES TESTING All the study hypotheses were established and confirmed with the results. H1 is established with the study results, which demonstrate that Conscientiousness people will show no addiction to SNPs (Beta = 0.09, p-value not significant). Additionally, H2 is sustained, which indicates that Neuroticism people may show more addiction to SNPs (Beta = 0.37, p-value < 0.001). Further, H3 is inveterate, this indicates that Openness to experience people may show more addiction to SNPs (Beta = 0.2, p-value < 0.001). Moreover, H4 asserted that Extraverted people may show more addiction to SNPs (Beta = 0.36, p-value < 0.001). Finally, the study results also confirmed H5, which indicates that Agreeableness people may show more addiction to SNPs (Beta = 0.23, p-value < 0.01).

The results show that there is no significant association between conscientiousness and SNPs. It is argued that those who score high on conscientiousness have control over their impulses and are orderly, diligent, and strive to achieve goals (Samarein et al., 2013). Conversely, unconscientious people are predisposed toward acting impulsively, being disorganized, and tend to procrastinate on tasks (Buckner et al., 2012). Hence, such characteristics can demonstrate their disinterest in being addicted to SNPs. This result is consistent with Wilson et al. (2010) and Andreassen et al. (2012) studies, who indicated that low conscientiousness scores significantly predicted both addictive tendencies and the time spent using SNPs. Also, this finding appears to be in line with previous research on the frequency of general Internet use in that people who score low on conscientiousness tend to use the Internet more frequently than those who score high on this personality trait (Landers & Lounsbury, 2004). Moreover, the study results supported the hypothesis that extraversion was positively related to SNPs. It is argued that people with high scores on extroversion seek out stimulation (Eysenck, 1967), thus this might

CONCLUSIONS, LIMITATIONS AND FUTURE RESEARCH Despite the increasing importance of SNPs, research into their addiction in relation to personality traits remains in its early stages (Griffiths, 2013). By incorporating both, psychological and technological perspectives, this study contributes to the literature of 190

Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(3):182- 195 (ISSN: 2141-7016) explain why Extroversion is associated with addictions in general (Hill et al., 2000). People who tend to be more anxious, lonely, and introverted used the Internet to compensate their real-world isolation in these early studies of Internet use (AmichaiHamburger & Ben-Artzi, 2003). This finding is in line with Andreassen et al. (2012) and Ross et al. (2009) studies that examined the relationship between extroversion and Facebook addiction, and confirm the notion that extroverts may use these platforms as a way of expressing their social needs and tendencies (Ross et al., 2009).

observation and non-self-report data; this could be investigated in future work. Fourth, this study did not examine the influence of gender or age differences on SNPs, an area that could be investigated in future work also. Fifth, while the brief scale that captures personality traits measures in this study showed adequate levels of validity, reliability and external correlation, future studies may use other personality traits measures such as the IPIP scales (Goldberg et al., 2006). Finally, though the current research model accounts for 53% variance of SNPs addiction, there is still much variance to be accounted for; future research could look at other factors that may contribute to SNPs addiction, such as self-esteem, loneliness, and depression.

This study also found neuroticism was positively associated with SNPs addiction. That is, people with greater levels of neuroticism and negative affectivity are more likely to suffer from SNPs addiction. Andreassen et al. (2013) argued that neuroticism may be a general vulnerability factor for the development of psychopathology. The authors also suggested that behavioural addictions may reflect a preference to do something alone to avoid feeling anxious. This finding supports prior research that have found greater levels of neuroticism were associated with instant messaging (Ehrenberg et al., 2008), Facebook use (Ross et al., 2009) and the usage of chat rooms (Hamburger & Ben-Artzi, 2000). Also, the study results show that there is a significant relationship between agreeableness and SNPs addiction. In reference to Weinstein and Lejoyeux (2010) and Graziano and Tobin (2009) work, Andreassen et al. (2013, p. 95) argued that people with behavioural addictions often come into conflict with others dueto their behaviour, which contradict with some of the basic characteristics of agreeableness, such as being likeable, pleasant, and emphasizingharmony in relations with others. Thus, the authors proposed that high scores on agreeablenessmay be a protective factor for developing behavioural addictions, due to a motive to avoid interpersonal conflicts.Finally, the results of this study demonstrated a significant relationship between Openness and SNPs addiction.This finding is in line with Correa et al. (2013) and Correa et al. (2010). The authors argued that this finding could be explained due to the novel nature of SNPs. This research, like any other, has its own set of limitations. First, while the study sample size provides acceptable statistical power, the sample size of this study still considered small. Therefore, future research should investigate cross-validation of the current study with larger samples. Second, the sample of the current study was draw from a homogenous group of students from only one university in Kuwait; this may limit the generalizability of the study results. Future research may be repeated in other universities in the GCC region and results could be compared with the current study. Third, this study derived the data based on self-reporting measures and did not include any objective measures such as direct

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