published quarterly by the university of borås, sweden

vol. 22 no. 3, September, 2017

How do personality traits shape information-sharing behaviour in social media? Exploring the mediating effect of generalized trust

Shengli Deng, Yanqing Lin, Yong Liu, Xiaoyu Chen, and Hongxiu Li

Introduction. Personality and trust have been found to be important precursors of information-sharing behaviour, but little is known about how these factors interact with each other in shaping information-sharing behaviour. By integrating both trust and user personality into a unified research framework, this study examines how trust mediates the effect of personality traits (specifically, agreeableness and conscientiousness) in triggering information-sharing behaviour in an online social networking environment.
Method.Integrating the Big Five theory of personality and the theory of generalised trust, a research framework is proposed for the determinants of information-sharing behaviour on social media. Data about personality, trust, and information sharing were collected from Chinese youths through an online survey.
Analysis.Structural equation modelling was applied to data from 311 valid questionnaires to verify the research framework.
Results. Both personality traits and generalised trust have a significant impact on information-sharing behaviour on social media, and generalised trust plays a mediating role between personality traits and information-sharing behaviour.
Conclusion.This research advances the understanding of why information is shared within social media contexts with regards to trust and personality traits. It also clarifies the connections between personality traits, information-sharing behaviour on social media, and generalised trust.


Information sharing, ‘a necessary element of knowledge management’, has been widely studied in the contexts of organisations and virtual communities, in which the flow of information is not restricted (Jarvenpaa and Staples, 2000, p. 130). For instance, information posted in a virtual community may be open to all members. Nowadays, restricted information flow seems to have become increasingly popular – as witnessed by the wide implementation of restricted audience functions in popular social media software (Kivran-Swaine, Govindan, and Naaman, 2011). As a result, whilst individual users establish contacts with many people through social media, they also try to control the direction of the flow of their information to different groups of people. In other words, individual users of social media tend to control what information they post and to whom when using social media. This new restricted information-sharing environment, in contrast to the conventional open environment, is a new context for research. In this regard, factors like trust may play a critical role in enabling information sharing when corresponding with people who have different personalities. There is a paucity of research about this; thus this research examines information sharing between users in a restricted information-sharing environment by quantifying the direct and mediating effects of both personality and affective and cognitive trust.

The development of social networking or online information-sharing applications makes them increasingly popular among young generations. Taking WeChat in China as an example, it is a smart, instant communication application that enables users to share text, voice, images, and video. WeChat offers a function for individuals to post Moments, providing a Twitter-like micro blogging platform, known as Pengyou Quan in Chinese, where individuals can share text, pictures, news, articles, music, small videos, and location data. Users can set the privacy of Moments to control the information flow in WeChat, and only those who are included in Pengyou Quan can comment on or like others’ posts (i.e., their Moments), whereas other contacts in WeChat cannot. As a mobile-based application, WeChat enables users to give comments and feedback in a timely manner. The penetration rate of WeChat is set to reach ninety-three percent in China’s first-tier cities, while sixty percent of its users come from younger generations, ranging from fifteen to twenty-nine years old (Tencent, 2015). Just five years after its inception, it has over 927 million registered users and 700 million monthly active users (Tencent, 2016).

WeChat facilitates the direct import of contact lists from phone contacts or other software. In addition, its functions like Shake, People Nearby, and Message in a Bottle allow users to establish networks with strangers, thereby expanding their scope of information sharing. As such, WeChat users create, exchange, and distribute a large number of different types of information. In this study, we explore how individuals’ personality traits affect their trust in social media as well as their possible effects in triggering online information-sharing behaviour.

Information-sharing behaviour on social media can be regarded as a process in which the individuals provide information reciprocally to all entities who may need it (Gardoni, Spadoni, and Vernadat, 2000), including comments, suggestions, and answers to questions raised (Rafaeli and Raban, 2005). The activity of information sharing is not a unilateral behaviour, but the behaviour of communicating and exchanging useful information among community members (Dawes, 1996), aimed at expanding the value of information or creating new information or knowledge (Hooff and Ridder, 2004). A number of studies on information-sharing behaviour are available, many of which focus on the relationship between interpersonal trust and information sharing (Beldad and Kusumadewi, 2015; Gupta and Dhami, 2015; Liu, Rau, and Wendler, 2015), or between personality traits and information or knowledge sharing (e.g., Guadagno, Okdie, and Eno, 2008; Matzler, Renzl, Müller, Herting, and Mooradian, 2008; Skues, Williams, and Wise, 2012). However, to the best of our knowledge, there is a lack of research that considers these three factors simultaneously in one integrated research framework. For instance, although trust is important in triggering online information-sharing behaviour, what actually motivates people’s trust? Even though people with different personality types can be distinguished by their resulting online information sharing, is the effect of personality type mediated by trust? Our study aims to answer these questions. Specifically, it explores how different personality traits (agreeableness and conscientiousness) shape the information-sharing behaviour (browsing, posting and replying behaviour) of individuals by applying generalised trust (including affective trust and cognitive trust) as a key mediator.

The rest of the paper is structured as follows: a literature review is presented in the next section, followed by a discussion of the research model and hypotheses. The research methodology and results of the data analysis are then presented.  The paper then discusses the implications of the results and highlights the research limitations and possible avenues for future research.

Literature review

Impact of personality traits on information-sharing behaviour in social media

One of the main research streams examining online information-sharing behaviour focuses on addressing the individual factors for information sharing by applying classical theories like social exchange theory, social cognitive theory, social capital theory, and the technology acceptance model (Lu and Hsiao, 2007; Pilerot, 2012). Lu and Hsiao (2007) investigated the information-sharing behaviour of individuals on blogs and found that self-efficacy and personal outcome expectations exert a significant impact on the intention to share information on blogs. Papadopoulosa, Stamatib, and Nopparuch (2013) explored the use of employee Weblogs for information sharing and found that self-efficacy, perceived enjoyment, certain personal outcome expectations, and individual attitudes towards knowledge sharing are positively related to the intention of knowledge sharing on employee Weblogs. Enjoyment, self-efficacy, learning, personal gain, altruism, empathy, and social engagement can encourage users to share information on different types of social media, such as Facebook, Twitter, Delicious, YouTube, and Flickr (Oh and Syn, 2015). In the context of online communities, it has been found that interpersonal trust, individual characteristics, and social relations all have significant impacts on information-sharing behaviour (Gupta and Dhami, 2015; Liu et al., 2015). Having a positive propensity to share and a belief that the information is your own property also leads to more media use and the sharing of the information (Jarvenpaa and Staples, 2000). Online information-sharing behaviour entails both human-machine interaction and human-human interaction, in which trust encourages people to engage in cooperative interaction (M. Lin, Hung, and Chen, 2009; Nahapiet and Ghoshal, 1998). Thatcher, Loughry, Lim, and McKnight (2007) noted that individual aspects like personality and demographic characteristics affect the beliefs and behaviour of information systems’ users.

Previous studies reported personality as an important dimension of online information-sharing behaviour. Personality is an individual system of intrinsic persistent characteristics, promoting the consistency of an individual’s behaviour (Pervin and John, 1990). According to psychological theories, personality refers to the integration of emotional, attitudinal, and interpersonal processes that originate from within each person and to each person’s temperamental and behavioural response patterns (Adali and Golbeck, 2012; Funder, 2012; Golbeck, Robles, and Turner, 2011; Heinström, 2003). Personality traits also differ because of differences among individuals’ experiences, such as their backgrounds and social experiences. Personality traits describe basic modules of the construction of personality, and play a role in influencing explicit behaviour and others’ perceptions (Pervin and John, 1990). Individuals with different personality traits have different attitudes towards social media and different ways of using them (Correa, Hinsley, and Zúñiga, 2010; Ryan and Xenos, 2011). The Big Five personality theory (Costa and McCrae, 1992) is one of the most popular theories in human personality research, wherein personality is composed of five traits, including neuroticism, extraversion, openness to experience (hereafter: openness), agreeableness, and conscientiousness.

Specifically, different dimensions of personality traits were found to have diverse influences on Internet use (Amichai-Hamburger, Wainapel, and Fox, 2002; Guadagno et al., 2008). Johnson and Johnson (2006) found that individuals with different traits exhibit a variety of preferences regarding network content. Barrick, Parks, and Mount (2005) reported that self-monitoring moderates the relationship between the Big Five personality traits and interpersonal performance. Personality traits were also found to significantly affect Facebook use among college students (e.g., Jenkins-Guarnieri, Wright, and Johnson, 2013; Kuo and Tang, 2014; Skues et al., 2012), and influence the online political engagement of undergraduate students (Quintelier and Leuven, 2013). Individuals with higher levels of neuroticism and openness were more likely to be blog authors, while individuals with different levels of neuroticism use blogs differently (Guadagno et al., 2008). For males, extraversion positively correlated with a preference for social interaction services while neuroticism negatively correlated with it (Amichai-Hamburger and Ben-Artzi, 2000). For females, extraversion was negatively related to the use of social services while neuroticism was positively related to it (Amichai-Hamburger and Ben-Artzi, 2000). Several studies indicated that personality traits directly affect people’s preferences in their use of social networking services (e.g., Kim and Chung, 2014; Uesugi, 2011). A number of studies examined the relationship between personality traits and network or real social interaction and reported significant differences in the networking and communicative behaviour of individuals with different personality traits (Amichai-Hamburger et al., 2002). Amichai-Hamburger and Ben-Artzi (2003) suggested that Internet use easily leads to user loneliness, and personality characteristics and loneliness are found to be significant indicators of well-being . In particular, individuals with a strongly neurotic personality are more likely to feel lonely and more inclined to use social media services on the Internet. A summary of prior studies on the effect of personality traits on social media use is provided in Table 1.

Table 1: A review of the effect of personality traits on social media use
Research context Main findings Sources
Social media Extraversion and openness to experiences positively relate to social media use, while emotional stability has a negative effect. Correa, Hinsley, and Zúñiga (2010)
Facebook Facebook users tend to be more extraverted and narcissistic, but less conscientious and socially lonely, than nonusers. Ryan and Xenos (2011)
Social communication on the Internet Introverted and neurotic people locate their "real me" on the Internet, while extroverts and non-neurotic people locate their "real me" through traditional social interaction. Amichai-Hamburger, Wainapel, and Fox (2002)
Blogs People who are high in openness to new experience and high in neuroticism are more likely to be bloggers. Guadagno Okdie, and Eno (2008)
E-communication Introversion-extroversion was not related to students’ preference for synchronous chat rather than asynchronous discussion Johnson (2006)
Personality Performance Self-monitoring moderates the relationship between big five personality traits (extraversion, emotional stability, and openness) and interpersonal performance. Barrick, Parks, and Mount (2005)
Facebook Only one dimension of personality (extraversion) was related to interpersonal competency and Facebook use when first accounting for attachment style. Jenkins-Guarnieri, Wright, and Johnson (2013)
Facebook People with high extraversion, low agreeableness and high openness tend to spend more times on Facebook and have more friends and photos. Kuo and Tang (2014)
Facebook Students with higher openness levels reported spending more time on Facebook and having more friends on Facebook. Extraversion, neuroticism, self-esteem and narcissism have no significant relationship with Facebook use. Skues, Williams, and Wise (2012)
Facebook Openness to experience and extraversion have an effect on online political engagement. Only small effects were observed for consciousness, agreeableness, and emotional stability. Quintelier and Leuven (2013)
Internet services Extraversion and neuroticism show different patterns of relationships with the factors of the Internet-Services Scale, with different patterns of association for men and women. For men, extraversion was positively related to the use of leisure services and neuroticism was negatively related to information services, whereas for women, extraversion was negatively related to neuroticism positively related to the use of services. Hamburger and Ben-Artzi (2000)
Social Networking Services Social networking service use moderates the effect of both extroversion and neuroticism on individual job satisfaction. Kim and Chung (2014)
Social Networking Services Extroversion and agreeableness influence the use patterns of social networking services, while attitudes toward protecting privacy indicated significant differences between extroversion, agreeableness, and conscientiousness and the reason for future use of services even having understood the dangers of privacy divulgence. Uesugi (2011)



Trust can be defined as ‘a psychological state comprising the intention to accept vulnerability based upon positive expectations of the intention or behaviour of another’ (Rousseau, Sitkin, Burt, and Camerer, 1998, p. 394). This refers to an individual’s confidence in the purpose, motivation, and sincerity of others when exploring an interpersonal relationship (Mellinger, 1956), which can be further subdivided into two dimensions including cognitive trust and affective trust (Lewis and Weigert, 1985). Specifically, cognitive trust refers to the cognitive judgments of the trusting party regarding the reliability and the ability of the trusted party (Lewis and Weigert, 1985). Some relevant factors are a prerequisite for affective trust, including cultural background, the strength of the relevant ability, personality traits, and intention. Furthermore, ‘this affective component of trust consists in an emotional bond among all those who participate in the relationship’ (Lewis and Weigert, 1985, p. 971). Therefore, affective trust is based on a mutual emotional connection.

Trust is especially important for facilitating information-sharing behaviour in virtual communities. Trust between people in virtual communities can be regarded as a tendency of community members to believe that other members will not do anything harmful to their interests (Tsai, Huang, and Chiu, 2012). In our study, generalised trust is defined as the belief in the good intent, competence, and reliability of members with respect to information sharing (Kankanhalli, Tan, and Wei, 2005; Mishra, 1996; Putnam, 1993). The degree of trust in others and generalised expectations are compartmentalised, resulting in different degrees of the tendency to trust (Hassan, Toylan, Semerciöz, and Aksel, 2012).

Generalised trust is a key factor determining online information-sharing behaviour (Liu et al., 2015). Previous studies highlighted that trust among members in virtual communities affected their intention to obtain and share information or knowledge (e.g., Chang and Chuang, 2011; Nahapiet and Ghoshal, 1998; Ridings, Gefen, and Arinze, 2002; Tsai and Ghoshal, 1998). People who have mutual trust are more willing to share their own ideas and comprehensive information (Bock, Zmud, Kim, and Lee, 2005). Interpersonal trust plays a vital role in creating a good atmosphere for information sharing. Furthermore, trust can create and maintain the exchange relationship, which in turn leads to high quality information and knowledge-sharing behaviour (Bai and He, 2016). Beldad and Kusumadewi (2015) investigated the impact of trust on location information-sharing behaviour among college students, and revealed that the use of specific location-sharing applications among students is partly attributable to competence-based trust in such applications and to their trust in the applications’ network members. Liu et al. (2015) explored the relation between trust and information sharing from a cross-cultural perspective, and found that interdepelndent individuals were more relationship-oriented in building their trust than independent ones. Wu, Hsu, and Yeh (2007) indicated that trust affects knowledge-sharing behaviour, since knowledge sharing activities are related to providing information, knowledge, and reciprocal resources to others. In studying social network sites, Bapna and Gupta (2011) argued that trust positively motivates the sustainable growth of interaction and information sharing among friends. In addition, both reciprocity and cooperation were found to promote mutual trust and that an accumulated experience of associated relationships has a long-term impact on generalised trust (Lindskold, 1978).

Lewis and Weigert (1985, p. 970) proposed that trust can be established in two different ways: building cognitive trust on trustworthy ‘good rational reasons’, and cultivating affective trust by maintaining emotional feelings between the consignor and consignee. Previous studies (Chowdhury, 2005; Mooradian, Renzl, and Matzler, 2006; Wu et al., 2007; Xu, Li, and Shao, 2012) highlighted that both cognitive trust and affective trust played a catalytic role in information sharing, and found that cognitive trust and affective trust predict voluntary information-sharing behaviour in online communities. Cultivating interpersonal trust is a challenge to online information-sharing behaviour, since building trust online is much more difficult than in an offline environment where face-to-face communication is enabled (Rocco, 1998; Wilson, Straus, and McEvily, 2006; Zornoza, Orengo, and Peñarroja, 2009). We summarize the key findings of prior studies on the relationship between trust and online information-sharing behaviour in Table 2.

Table 2: A summary of prior studies on the relationship between trust and online information-sharing behaviour
Research context Main findings Sources
Facebook Users’ trust in the ability of using Facebook increases their willingness to share information. Perceived security and perceived privacy are positively related to perceived trust in Facebook. Gupta and Dhami (2015)
Online communication media People’s interpersonal trust and online information-sharing performance differ from different cultural perspectives (China and German). Liu, Rau, Wendler (2015)
Virtual community Reputation, social interaction, and trust have positive effects on the quality, but not the quantity, of shared knowledge. Chang and Chuang (2011)
virtual communities Trust has a downstream effect on members' intentions to both give information and get information through the virtual community. Ridings, Gefen, and Arinze (2002)
Intra-firm Networks Trust is significantly related to the extent of inter-unit resource exchange. Tsai and Ghoshal (1998)
Location sharing application (LSA) Students' usage of a specific LSA could be attributed to competence-based trust in LSA and to their trust in LSA network members. Beldad and Kusumadewi (2015)
E-travel industry The affect-based trust in a team positively relates to the degree of knowledge sharing and learning intensity in the team. Wu, Hsu, and Yeh (2007)
Facebook Positive interaction and information-sharing among friends can motivate a sustainable growth of trust. Bapna and Gupta (2011)
Organization Interpersonal trust (including both affect-based and cognition-based trust) has positive influence on complex knowledge sharing. Chowdhury (2005)
Organization Context-specific individual factors (including interpersonal trust and personality) influence knowledge sharing. Mooradian, Rentzl, and Matzler (2006)
Organization Affect-based and cognition-based trust have impact on the extent to which staff members are willing to share and use tacit knowledge. Holste and Fields (2010)
Virtual Communities Attachment motivation, social support orientation, and disposition to trust influence trusting beliefs and citizenship knowledge-sharing behaviour. Xu, Li, and Shao (2012)
E-communication In electronic contexts, the pre-meeting Face-to-Face communication can positively promote trust. Rocco (1998)
Computer-mediated teams High levels of inflammatory remarks were associated with slow trust development in computer-mediated teams. Wilson, Straus, and McEvily (2006)
Virtual teams Group trust climate moderates the relationship between the virtuality level and group process satisfaction and group cohesion when the virtuality level is high. And relational capital plays an important role in virtual teams’ effectiveness. Zornoza, Orengo, and Peñarroja (2009)

Research model and hypotheses

Allport (1937, p. 48) regarded personality as ‘the dynamic organization with the individual of those psychophysical systems that determine his unique adjustments to his environment’. Personality reflects a behavioural tendency that is relatively consistent in different situations and at different times (Allport, 1937). This tendency can either generate or guide human behaviour, resulting in individuals performing the same action when facing different types of stimulation (Barrick and Mount, 1993; McCrae and Costa, 1997). Extant literature provides several theoretical models on personality traits (Cattell and Cattell, 1995; Cattell, 1943; Costa and McCrae, 1992; McCrae and Costa, 1997; Pickford, Eysenck, and Notcutt, 1954; Smillie et al., 2009; Zuckerman, 1994). As discussed above, the Big Five model (McCrae and Costa, 1997) is one of the most widely accepted for measuring the different dimensions of personality traits, and divides personality traits into five different dimensions, including neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. The NEO Personality Inventory (NEO PI) is a widely used measurement for the five-factor model of personality; it provides five personality domain scores that correspond to five broad dimensions of personality (Bagby and Marshall, 2003). It was further modified into the revised NEO Personality Inventory (NEO PI-R) (Costa and McCrae, 1992). The reliability of the Big Five model has been demonstrated in a large number of studies including different cultural backgrounds (Poortinga, Vijver, and Hemert, 2002; Rolland, 2002; Rossier, 2005).

Previous studies indicated that personality traits have a strong impact on information behaviour (Heinström, 2003). Personality traits affect people’s willingness to share personal information (Balmaceda, Schiaffino, & Godoy, 2013). Specially, individuals with lower average level of neuroticism, but higher average level of personality traits of openness to experience, agreeableness and conscientiousness, are more salient in communicating and sharing information in social networking (Balmaceda et al., 2013; Gunduz & Demirhan, 2014). Furthermore, higher scores in openness to experience and upright agreeableness motivate a higher level of willingness for people to share information (Marshall, Lefringhausen, & Ferenczi, 2015).


Agreeableness refers to the degree to which an individual is easy to get along with, reflecting the individual value of cooperation and interpersonal harmony (Tommasel, Corbellini, Godoy, and Schiaffino, 2015). Agreeableness describes the propensity for an individual to be altruistic, trusting, modest, warm, and exhibit a ‘prosocial and communal orientation’ (John and Srivastava, 1999, p. 121). Studies by Graziano and Tobin (2002) and Johnson and Krueger (2004) indicate that agreeableness includes properties missing from extraversion, like friendly and warm. The essence of agreeableness is altruism, through which individuals are likely to be eager to help others (Liao and Chuang, 2004; McCrae and Costa, 1997). Therefore, individuals with high scores in agreeableness tend to be more helpful, forgiving, courteous, cooperative, trustworthy, and compassionate (Rothmann and Coetzer, 2003; Tommasel et al., 2015) and more inclined to initiate cooperation than competition (Mount, Barrick, and Stewart, 1998). In other words, being agreeable entails getting along with others and satisfying relationships (Organ and Lingl, 1995). Thus, it is possible that individuals with high levels of agreeableness are more likely to be helpful and cooperative with others and therefore share information with others. Accordingly, we hypothesise that:

H1: Agreeableness is positively associated with information-sharing behaviour.

‘'Agreeableness seems to be the most consistent predictor of one’s level of trust’ (Gerris, Delsing, and Oud, 2010, p. 56). Because agreeableness reflects a person’s orientation to be cooperative and to care about the well-being of others it is seen as a predictor of trust (Allik and McCrae, 2002; Gerris et al., 2010; Goldberg, John, Kaiser, Lanning, and Peabody, 1990; Goldberg, 1992). Individuals with high scores in agreeableness possess, for example, sympathy, inconspicuousness, a gentle disposition (Goldberg, 1993; Saucier and Ostendorf, 1999), propensity to trust, straightforwardness, and altruism (Allik and McCrae, 2002; Costa and McCrae, 1992; McCrae, 2004). People with high levels of agreeableness are also inclined to be kind-hearted, helpful, and trusting, whereas people with low levels of agreeableness are inclined to be ruthless, overly suspicious, and uncooperative (Guadagno et al., 2008). Notwithstanding being genetically determined, agreeableness is found to be associated with childhood experiences (Graziano, Jensen-Campbell, and Hair, 1996; Jensen-Campell et al., 2002; MacDonald, 1995), producing correspondingly positive and negative life outcomes. For example, highly agreeable individuals are more likely to acquire more and better interpersonal relationships and interaction (Asendorpf and Wilpers, 1998; Graziano et al., 1996), better performance evaluations (Hurley, 1998; Hurtz and Donovan, 2000; Mount et al., 1998) and be more inclined to help others (Colbert, Mount, Harter, Witt, and Barrick, 2004; King, George, and Hebl, 2005). In other words, they are more willing to trust others. Hence, people with strong agreeableness as part of their personality are more likely to have a high level of generalised trust (Konovsky and Organ, 1996). Mooradian et al. (2006) found that agreeableness positively related to interpersonal trust. Therefore, we hypothesise that:

H2: Agreeableness is positively associated with generalized trust.

Conscientiousness refers to one’s goal and achievement orientation (Gerris et al., 2010). People with high scores in conscientiousness tend to control, manage, and regulate their own impulsion relatively well, representing the ability for self-discipline and the motivation to address achievement and responsibility (McCrae and Costa, 1997). Conscientious people tend to pursue achievement-oriented value and have a sense of responsibility (Rothmann and Coetzer, 2003). To accomplish their goals, they often have a strong will and motivation to help others and engage in organisational behaviour outside the work context (Costa and McCrae, 1992; Organ and Ryan, 1995). A number of studies pointed out that the personality trait of conscientiousness had a significant influence on information and knowledge sharing (e.g., Matzler, Renzl, Mooradian, Krogh, and Mueller, 2011; Matzler et al., 2008). For instance, a positive correlation was found between conscientiousness and organisational citizenship behaviour (Organ, 1994). Individuals with high conscientiousness exceed the work responsibilities and demands of a contract (Organ and Ryan, 1995). This means that individuals with a high level of conscientiousness are more inclined to spend time and energy recording their knowledge and information so that they can share with others (Matzler et al., 2011). Therefore, we hypothesise that:

H3: Conscientiousness is positively associated with information-sharing behaviour.

To achieve their target goal, conscientious individuals tend to be frank, candid, disciplined, organised, methodical, able to use self-restraint, persevering, strict, and hardworking (Ping, Mujtaba, Whetten, and Wei, 2012). Conscientious individuals are consistent, predictable, non-impulsive, and therefore trustworthy (Costa and McCrae, 1992; Goldberg, 1992). Gerris et al. (2010) found that conscientiousness emerged as the most important predictors of dyadic trust, or mutual trust between two people, and an individual’s perception of his/her partner’s conscientiousness in an established marriage is a salient predictor of their own trustworthiness . Ping et al. (2012, p. l010) suggest that individuals with high scores in conscientiousness always perform in accordance with a plan and persevere, and ‘would easily win higher-level approval from subordinates through their behaviour, and the manner and detail can provide more credible evidence for trust’. Taking an inductive approach to examining the relationship of a leader’s personality traits and upward trust with respondents in Chinese culture, the study by Ping et al. showed that conscientiousness positively influenced both affect-based and cognition-based upward trust. Arguably, the more conscientious someone is, the more generalised trust they may exhibit. In other words, an individual who possesses strong conscientiousness is more inclined to trust others. Therefore, we hypothesise that:

H4: Conscientiousness is positively associated with generalized trust.

People differ in terms of their tendency to trust others (Evans and Revelle, 2008), which may stem from the individual differences in their personality traits formed in childhood and affected by their physical and mental development. In the process of growing up, the conception of individuals is constantly generalised and transferred by interacting with society, resulting in a certain fixed and expected behaviour pattern. Because of differing backgrounds in upbringing and social experience, individuals differ in their degree of trust in others. In the processes of communicating and interacting, the trust of both interacting sides is beneficial for the sharing and exchanging of information (Thompson, 1991), reducing uncertainty (Kollock, 2010), and increasing the intention to cooperate (Mayer andi Davis, 1995; Smith, Carroll, and Ashford, 1995). Based on social exchange theory, the closer the relationship among individuals, the more willing they are to share information with each other, and trust is a key element for measuring relationships (Morgan and Hunt, 1994). Trust is one of the key factors affecting the intention to share information (Ebrahim-Khanjari, Hopp, and Iravani, 2012; Lin et al., 2013). Asking for advice or information from others may hurt one’s self-esteem and reputation, but having sufficient trust helps convince the other party of one’s concern, compassion, goodwill, and sincerity, enabling sharing behaviour. Thus, trust helps form a mutually beneficial, friendly, and harmonious atmosphere for information sharing, exchange, and interaction (Morgan and Hunt, 1994). Therefore, we hypothesise that:

H5: Generalized trust is positively associated with information-sharing behaviour.

Research framework

Based on the five hypotheses above, a research framework is established, as shown in Figure 1.

Figure1: Research framework for information-sharing behaviour on social media
Figure1: Research framework for information-sharing behaviour on social media


Research methodology


A questionnaire was administrated to collect empirical data. The questionnaire’s items were primarily developed on the basis of the scales used in previous studies (Chang and Chuang, 2011; Chiu, Hsu, and Wang, 2006; Costa and McCrae, 1992; Davenport and Prusak, 1998; Hsu, Ju, Yen, and Chang, 2007; Lewis and Weigert, 1985; McCrae and Costa, 1997; Xu, M and Ye, 2011). A five-point Likert scale (1=strongly disagree to 5=strongly agree) was used to measure each item. Based on studies by Hsu et al. (2007), Davenport and Prusak (1998), and Xu, M and Ye (2011), information-sharing behaviour is divided into three specific dimensions in this study, including browsing behaviour, posting behaviour (i.e., initiating discussions), and replying behaviour (i.e., replying to existing topics). The questionnaire is in Appendix A.

WeChat users were recruited to test the research framework because of the popularity of WeChat among potential participants (i.e., Chinese computer users). Structural equation modelling technique was used to test the research framework with Smart Partial Least Squares (Hansmann and Ringle, 2004), which is also suitable for models with formative constructs and relatively small samples (Gefen, Rigdon, and Straub, 2011). Based on the recommended procedure (Hulland, 1999), we assessed the reliability and validity of each latent variable measurement as well as the paths between the constructs and their significance level.

Sampling and data collection

The questionnaire was advertised online in January 2016 through different social networking platforms. Within two weeks, 339 questionnaires were returned. Incomplete or poorly filled in questionnaires were excluded, such as those submitted within less than 3 minutes of opening, resulting in a total of 311 valid samples retained for later data analysis. Because the survey was mainly advertised and posted on a university Website and email list, most participants are from young generations. Note that young generations are the main users of social media (e.g., Cheung, Chiu, and Lee, 2011). For instance, 87.1% of social media users utilize WeChat and more than 50% of them have a degree in high education (Sun, Wang, Shen, and Xi, 2015). The demographic information of the respondents is provided in Table 3. As shown there, the participants include 131 (42.1%) men and 180 (57.9%) women, and most of them are between 20 to 23 years old. A majority of the respondents have used WeChat for more than 1.5 years (77.8%). About 291 (93.6%) respondents use WeChat on a daily basis, and features such as Chats and Moments were most frequently used by the respondents in their daily use. These two features were mainly used to express their own emotions and to obtain information from their friend networks. The majority of respondents indicated that emotional communication (75.2%), chats with friends (72.0%) and recreation (59.5%) were the main reasons for them using WeChat.

Table 3: Demographic details of respondents
  Measurement Samples     Measurement Samples
Sex Male 131 (42.1%)   Purpose of use Emotional communication 234(75.2%)
Female 180 (57.9%) Chat with friends 224(72.0%)
Age (full year) <20 29 (9.3%) Recreation 185(59.5%)
20~21 62 (20.0%) Sharing 177(56.9%)
22~23 159 (51.1%) Learning 108 (34.7%)
>23 61 (19.6%) Marketing and shopping 22 (7.1%)
Function of use Chats 291 (93.6%) Know about news 80 (25.7%)
Moments 266 (85.5%) Others 2 (0.6%)
Scan QR code 135 (43.4%) Experience of use Less than 6 months 20 (6.4%)
Shake 25 (8.0%) 6 months -1years 15 (4.8%)
Drift bottle 9 (2.9%) 1 -1.5 years 34 (11.0%)
Quick payment 143 (46.0%) More than 1.5 years 242 (77.8%)
Used as a game account 19 (6.1%) Frequency Less than per week 10 (3.2%)
Used as a game account 15 (4.8%) 1~3 times per week 11 (3.5%)
    4~5 times per week 22 (7.1%)
    Use every day 268 (86.2%)

Data analysis and results

Reliability and validity

Measurement reliability reflects the consistency and stability of a tested measurement (Cook and Campbell, 1979), which can be assessed by checking its composite reliability and average variance extracted (Fornell and Larcker, 1981). As shown in Table 4, composite reliability values for all the constructs were greater than 0.8, and all average variance extracted values were greater than 0.5, exceeding the suggested threshold values of 0.7 and 0.5, respectively (Fornell and Bookstein, 1982; Fornell and Larcker, 1981). All Cronbach's Alpha values were above 0.7 except for the construct of Posting (0.692), which was very close to 0.7, indicating the measurements are reliable.

Table 4: Reliability of Constructs
  Mean S.D. Cronbach's Alpha CR AVE
CON 3.742 0.654 0.745 0.835 0.563
AGR 3.561 0.723 0.781 0.854 0.594
AFFT 3.276 0.774 0.830 0.881 0.598
COGT 3.478 0.592 0.715 0.823 0.539
POS 2.872 0.811 0.692 0.830 0.623
REP 3.218 0.772 0.766 0.865 0.681
BRO 2.891 0.922 0.871 0.920 0.793
Note: SD: standard deviation; CR: composite reliability; AVE: average variance extracted; CON: conscientiousness; AGR: agreeableness; AFFT: affective trust; COGT: cognitive trust; POS: posting; REP: replying; BRO: browsing.

A principal components analysis and varimax rotation were performed. Convergent validity was assessed by checking loadings to see whether items within the same construct correlate highly with one another. The discriminant validity of the constructs was assessed by examining the factor loadings; items should be loaded higher on their intended constructs than on other constructs (Cook and Campbell, 1979). The approach to calculating discriminant validity is to compare the square root of the average variance extracted for a construct and the correlation coefficients related to that construct. As shown in Table 5, the square roots of average variance extracted values for all the constructs were greater than the correlation coefficients, suggesting that all constructs had good discriminant validity (Bock et al., 2005). Comrey (1995) suggested that loadings from 0.45 to 0.54 indicated fair, from 0.55 to 0.62 indicated good, from 0.63 to 0.70 indicated very good, and above 0.71 indicated excellent discriminant validity. As shown in Table 6, the item loadings on their respective constructs were mostly higher than 0.70, suggesting that these constructs had excellent convergent and discriminant validity.

Table 5: Correlational coefficients
AFFT 0.773              
AGR 0.225 0.771            
BRO -0.295 0.046 0.891          
COGT 0.583 0.207 -0.071 0.734        
CON 0.256 0.562 0.032 0.249 0.750      
POS 0.521 0.136 -0.187 0.331 0.118 0.789    
REP 0.602 0.226 -0.229 0.398 0.307 0.600 0.825  
SHARE 0.433 0.223 0.358 0.351 0.251 0.741 0.735  

Note: CON: conscientiousness; AGR: agreeableness; AFFT: affective trust; COGT: cognitive trust; POS: posting; REP: replying; BRO: browsing. SHARE: information-sharing (second-order formative variable). The boldfaced numbers in the diagonal row are the square roots of the average variance extracted values.

Table 6: Loadings and cross-loadings
AFFT1 0.768 0.236 -0.307 0.440 0.257 0.536 0.522
AFFT2 0.828 0.117 -0.334 0.410 0.146 0.561 0.507
AFFT3 0.803 0.111 -0.251 0.439 0.152 0.454 0.536
AFFT4 0.697 0.184 -0.071 0.477 0.210 0.279 0.312
AFFT5 0.764 0.220 -0.204 0.497 0.225 0.286 0.447
AGR1 0.216 0.742 -0.009 0.261 0.438 0.113 0.194
AGR2 0.118 0.704 0.130 0.133 0.286 0.049 0.089
AGR3 0.140 0.780 -0.007 0.156 0.443 0.103 0.188
AGR4 0.181 0.852 0.016 0.148 0.529 0.108 0.201
BRO1 -0.217 0.090 0.890 -0.002 0.109 -0.205 -0.161
BRO2 -0.274 0.061 0.906 -0.062 0.005 -0.203 -0.201
BRO3 -0.322 -0.060 0.878 -0.159 -0.055 -0.203 -0.286
COGT1 0.560 0.200 -0.161 0.733 0.170 0.362 0.435
COGT2 0.232 0.104 0.119 0.632 0.180 0.117 0.092
COGT3 0.505 0.171 -0.123 0.826 0.146 0.333 0.320
COGT4 0.345 0.114 -0.013 0.734 0.251 0.186 0.25
CON1 0.142 0.529 -0.029 0.209 0.706 0.135 0.231
CON2 0.128 0.337 0.050 0.111 0.589 0.062 0.106
CON3 0.241 0.426 0.001 0.280 0.839 0.117 0.280
CON4 0.223 0.425 0.041 0.253 0.840 0.064 0.258
POS1 0.394 0.089 -0.098 0.208 0.044 0.822 0.456
POS2 0.373 0.168 -0.074 0.208 0.124 0.786 0.460
POS3 0.510 0.052 -0.335 0.371 0.122 0.748 0.558
REP1 0.518 0.236 -0.248 0.311 0.239 0.613 0.827
REP2 0.428 0.180 -0.134 0.359 0.254 0.387 0.789
REP3 0.540 0.145 -0.213 0.356 0.266 0.541 0.857
Note: CON: conscientiousness; AGR: agreeableness; AFFT: affective trust; COGT: cognitive trust; POS: posting; REP: replying; BRO: browsing

Information sharing, as a second-order formative variable, was measured using three first-order reflective variables (browsing, posting, and replying). Based on the studies by Davenport and Prusak (1998), Wu et al., (2007), and Xu, M and Ye (2011), browsing, posting, and replying behaviour were measured using reflective items and are thus reflective constructs. The formative variables were examined by checking their weights, loadings, and variance inflation factors (Petter, Straub, and Rai, 2007). As shown in Table 7, two weights for posting (called POS in Table 7) and replying (or REP) are highly significant, whereas browsing (or BRO) has an insignificant weight value (p<0.1). Further analysis showed that loadings for the three items of browsing were above 0.80 and significant, suggesting that these browsing items were of high importance (Cenfetelli and Bassellier, 2009). In addition, multicollinearity among the first-order reflective variables was examined, revealing that multicollinearity is not a concern because the variance inflation factors for the three first-order variables were below 5.0 (Hair, Anderson, Tatham, and Black, 1998). Given the importance of content validity for the formative factors (Bollen and Lennox, 1991; Petter et al., 2007), this variable was retained. Interestingly, a negative weight of browsing was found (weight=-0.419, t=1.524). A closer examination of this variable indicated that browsing can be considered a reversal of information sharing on social media (such as WeChat): when a subject said that s/he ‘often browses for all kinds of information using WeChat (such as Moments), but never posts’, this implied unilateral information behaviour because s/he had not yet been active in information sharing and thus lacked deep interaction.

Table 7: Weights and t-Statistics of formative constructs
First-order Reflective Variables Weights t-Statistics VIF
BRO -0.419 1.524 1.013
POS 0.413 11.063 1.775
REP 0.476 11.986 1.782

Note: POS: posting; REP: replying; BRO: browsing; VIF: variance inflation factors.

Hypotheses tests

Previous studies indicated that gender, age, education background, and other personal factors may affect information-sharing behaviour (Deng and Y. Lin, 2015; Jarvenpaa and Staples, 2000). Therefore, we included gender, age, major, and dating status as control variables in the research model. This effort helps determine that the significant results obtained in the study are not caused by the co-variation of those demographic features among the participants.

Figure 2 shows that agreeableness (β=0.126, p<0.01) and conscientiousness (β=0.234, p<0.001) significantly affect generalised trust, which in turn has a significant impact on information sharing (β=0.446, p<0.001). To test the mediating effect of the generalised trust, we employed the approach introduced by Baron and Kenny (1986). As shown in Figure 3, it is suggested that a variable functions as a mediator when it meets the following three conditions: (1) the independent variables significantly affect the mediating variable (Path a); (2) the mediating variable significantly affects the dependent variable (Path b); and (3) when Path a and Path b are controlled, a previously significant relationship between the independent variable and the dependent variable (Path c) is no longer significant, with the strongest demonstration of mediation occurring when Path c is zero. With regard to the last condition, we may envisage a continuum. When Path c is reduced to zero, we have strong evidence for a single, dominant mediator. If the residual Path c is not zero, this indicates the operation of multiple mediating factors. Our first step was to test the direct effect of agreeableness and conscientiousness on information sharing. As shown in Table 8, the results showed that the direct effect of agreeableness was not significant (β=0.077, p>0.1), suggesting that there was no mediating effect. Conscientiousness (β=0.164, p<0.01) had a significant effect on information sharing, but the variable’s direct effect on information sharing was insignificant when generalised trust was included (β=0.025, p>0.1), suggesting a full mediating effect for generalised trust.

Figure 2: The Revised Research Model
Figure 2: The Revised Research Model

Figure 3:Mediator Model (Baron&and Kenny, 1986)
Figure 3:Mediator Model (Baron&and Kenny, 1986)

Table 8: Mediating Effects of Generalized Trust (Baron & Kenny, 1986)
IV M DV IV→DV(c) IV→M(a) IV+M→DV Mediation
IV→DV(c’) M→DV(b)
CON TRUST SHARE 0.164** 0.234** 0.025(ns) 0.577*** Full
AGR TRUST SHARE 0.077(ns) 0.124* -0.007(ns) 0.577*** NA
Note: IV: independent variable; M: mediator; DV: dependent variable; CON: conscientiousness; AGR: agreeableness; TRUST: generalised trust; SHARE: information-sharing behaviour; *: p<0.05, **: p<0.01, ***: p<0.001; NA means there is no mediation effect between IV and DV; c means the path c between IV and DV when M is excluded in the model; c’ means the path c between IV and DV when M is included in the model.

Further analysis was conducted to ensure significant results and account for covariation with control variables. The control variables (gender, age, major, dating status) were included in the structural equation model. Almost all control variables had no significant impact on information-sharing behaviour, as shown in Figure 2. Hence, the results of the tests of the hypotheses were revealed to be stable and independent of control variables.


Discussion and implication


This study investigated the mediating effect of generalised trust on the relationship between personality traits and information-sharing behaviour in social media based on the Big Five personality theory and trust theory. We found that personality traits (agreeableness and conscientiousness) have significant impacts on information-sharing behaviour in social media and that differences are reported with regard to the effects of the different dimensions of personality traits. Specifically, conscientiousness has a direct and significant impact on information-sharing behaviour, while agreeableness affects information-sharing behaviour indirectly through the mediating role of generalised trust.

Based on our findings, agreeableness is not positively associated with information-sharing behaviour in social media (β = 0.077, ns.); thus, H1 is not supported. This finding does not match the findings of the work of Kuo and Tang (2014), who suggested that users with low agreeableness tended to have higher Facebook use and activity, since they used Facebook as a surrogate for real life social activities. Landers and Lounsbury (2006) also found that individuals with the trait of agreeableness dislike using the Internet. In the present study, agreeableness was found to be positively associated with generalised trust (β=0.126**, p<0.01), and generalised trust is positively associated with information-sharing behaviour on social media (β=0.446***, p<0.001). The above findings suggest that agreeableness has no direct influence on information-sharing behaviour; however, there is a significant but indirect effect from agreeableness on information-sharing behaviour mediated by generalised trust. The findings highlight the importance of generalised trust in understanding online information-sharing behaviour.

The insignificant relationship between agreeableness and information-sharing behaviour may result from the research context of this study. WeChat emphasizes the attribute of strong relationships and is semi-private, which results in restricted information flow. It is different from Facebook and Weibo, which are information-oriented; WeChat mainly focuses on relationship development, which reduces maintenance costs among the public, making the emotional connection among people more like to face-to-face communication. Thus, WeChat users, no matter whether they are agreeable or not, are focused more on relationship development with others in their Pengyou Quan in WeChat, resulting in generated trust, but not necessarily resulting in sharing information with others.

In contrast to agreeableness, we found that conscientiousness is positively associated with information-sharing behaviour in social media (β=0.164**, p<0.01), supporting H3. In other words, the results indicate that WeChat users who are more conscientious (i.e., more reliable, disciplined, organised, rule-following and capable of using self-restraint) are more likely to share information with others in WeChat use. In prior literature, no consistent finding on the impact of conscientiousness on social media use was found. Some research found that those with high conscientiousness were more willing to engage in sharing knowledge (Matzler et al., 2011), but conscientiousness was also found to be negatively associated with online social network use (Ryan and Xenos, 2011). One possible explanation for the significant positive impact of conscientiousness on information-sharing behaviour in social media can be that the restricted quality of WeChat for friends and information flow offers clear rules for individual users to exhibit self-control and thus appeals more to conscientious users. It also indicates that WeChat might fit with the conscientiousness personality trait of individual users.

Conscientiousness was found to be positively associated with generalised trust (β=0.234***, p<0.001), supporting H4. This finding is consistent with the prior finding that individuals with high conscientiousness will show a higher level of generalised trust in organisations (Witt, Burke, Barrick, and Mount, 2002). The reason for this may be that such individuals follow rules and think that other WeChat users, such as their Pengyou Quan, will also follow the restricted setting environment in WeChat for friends and information flow, thus generating trust in WeChat.

Trust has been considered a key prerequisite for the success of network information-sharing (Liu et al., 2015). In the present study, generalised trust is found to mediate the effects of personality traits on information-sharing behaviour in a social media environment (CON—TRUST: β=0.234***, p<0.001; CON—SHARE: β=0.025(ns); TRUST—SHARE: β=0.577***, p<0.001), indicating the full mediating effect of generalised trust between conscientiousness and information-sharing behaviour in social media. Also, those with high conscientiousness are more willing to engage in sharing knowledge (Matzler et al., 2011). The more generalised trust that members have toward each other, the less they will worry about the loss of their own competitive advantage, thus motivating information-sharing behaviour (Carminati and Ferrari, 2009).


This study reported the significant impact of personality traits and generalised trust on information-sharing behaviour and contributes to new insights in understanding online information-sharing behaviour from the integrated perspective of personality traits and trust. In addition, the significant mediating role of generalised trust indicated that trust is not only a determinant of information-sharing behaviour, but also a mediator to explain the impact of personality traits on information-sharing behaviour in social media. This study therefore makes the following theoretical contributions.

First, compared to previous research, this study measured information-sharing behaviour on social media as a second-order reflective latent variable derived from three dimensions, including browsing, posting, and replying behaviour, and this enriches prior research studies defining information-sharing behaviour as a potentially integral whole.

Second, this study advances theoretical development in understanding information-sharing behaviour in a social media context from the perspectives of trust and personality traits. The results highlight the importance of personality traits (agreeableness and conscientiousness) and generalised trust in understanding information-sharing behaviour in social media. Prior studies have focused on studying personality or trust respectively; our study integrates personality traits and trust in predicting information-sharing behaviour, and explains how trust mediates the impact of personality traits on information-sharing behaviour and helps to predict information-sharing behaviour. This offers a deeper understanding of the trust mechanism in triggering information-sharing behaviour in social media together with personality traits and clarifies the connection between personality traits, information-sharing behaviour on social media, and trust.

Third, this study offers further evidence that trust plays a critical role in predicting information-sharing behaviour among individual users of social media. This research was conducted on WeChat, a Chinese social platform with a restricted environment for information sharing and more privacy settings for controlling information flow than the conventional, open environment of Facebook.

The findings of this study have several implications for operators wishing to understand information-sharing behaviour. Social media operators need to be aware of the differences between individuals and should consider differences in personality traits and trust. Personality factors and generalised trust have a strong impact on information-sharing behaviour when using online social media. With such an understanding in mind, operators can interpret user behaviour more accurately. We hope that the findings of the study offer useful insights for the marketing departments of enterprises. For example, operators can conduct layered management for user segmentation. Based on the characteristics and properties of different users, practitioners could push related content or periodically publish some attractive topics to increase information interaction among users and do so by addressing target groups that have formed according to individual differences in personality traits and how those users trust others. Even though prior studies indicated that users with particular personalities are more likely to engage in social media use, the significant mediating role of trust should not be ignored. If a social media provider cannot build trust among users, users are more inclined to limit the information they share on the platform. Furthermore, social service providers can provide a communication platform that can build independent communication circles, facilitating users in the classifying and differentiation of the shared object and target. Prior studies show that the personality of a user of social media can be determined by analysing their digital records, which in turn facilitates operators wishing to develop relevant business strategies (e.g., Kosinski et al., 2013). In addition, strategies are needed to protect and raise cognitive and affective trust among community members.

Limitation and future studies

The paper has several limitations. Firstly, previous studies have provided a list of possible personality traits while our study only investigated two of them (agreeableness and conscientiousness). Interesting findings may be achieved by including more personality traits in the analysis. The explanation for why only two of the Big Five personality traits were considered is that the other three factors’ degree of fit with the model was insufficient. In summary, we hope that the results of our study are useful in encouraging future research that will extend the Big Five model by adding variables and more closely examining why the relationships exist in the model. Moreover, this study examined Chinese social media users; hence caution should be taken when generalising the results to users from other cultural backgrounds.


This research is supported in part by Key Research Institutes of Philosophy and Social Science by Ministry of Education, PR China (15JJD870001), Major Projects of the National Social Science Fund, PR China (14ZDB168&15ZDC025) and Luo Jia Youth Scholar of Wuhan University.

About the authors

Shengli Deng (corresponding author) is a professor at the Department of Information Management, School of Information Management at Wuhan University. He received his B.S. and M.S. in Information Management from Central China Normal University and PhD in Information Science from Wuhan University. His research interests include information behaviour, information interaction, and information services. He can be contacted at: victorydc@sina.com
Yanqing Lin is a postgraduate student of library and information science at the School of Information Management at Wuhan University. She received her B.S. in Information Management from Southwestern University. Her research interests include social networks and information behaviour. She can be contacted at: linyanqingswu@163.com
Yong Liu is an assistant professor at the Department of Information and Service Economy at Aalto University School of Business. He received his PhD in Science of Business Administration and Economics from Åbo Akademi University. His research interests include information systems’ user behaviour, e-commerce, social networks, and big data social science. He can be contacted at:Yong.liu@aalto.fi
Xiaoyu Chen is a PhD student at the Wee Kim Wee School of Communication & Information, Nanyang Technological University, Singapore. He received his M.S. in Library and Information Science from Wuhan University. His research interests include users' information behaviour in social media and human-computer interaction. He can be contacted at XIAOYU001@e.ntu.edu.sg
Hongxiu Li is a post-doctoral researcher at Turku School of Economics, University of Turku, Finland. She received her PhD from Turku School of Economics, University of Turku, Finland. Her research interests include information system adoption and post-adoption behaviour in the fields of e-commerce, e-services and mobile services in different research contexts. She can be contacted at:hongli@utu.fi


How to cite this paper

Deng, S., Lin, Y. , Liu, Y., Chen, X. & Li, H. (2017). How do personality traits shape information-sharing behaviour on social media? Exploring the mediating effect of generalised trust. Information Research, 22(3), paper 763. Retrieved from http://InformationR.net/ir/21-1/paper763.html (Archived by WebCite® at http://www.webcitation.org/6tTRhDgQy)

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Survey Items

Category Items Measurement Resource
Information sharing behavior Browsing I often browse all kinds of information using WeChat (such as Moments), but never post. Xu, M and Ye, 2011;Hsu, Ju, Yen, and Chang, 2007; Davenport and Prusak, 1998
I like to browse all kinds of information using WeChat (such as Moments), But I do not like to release personal information and reply.
I often browse all kinds of information using WeChat (such as Moments), but do not share or communicate with others.
Posting I often post the problems encountered in study or work to the chat groups or Moments on WeChat in order to get help Xu, M and Ye, 2011; Hsu, Ju, Yen, and Chang, 2007; Davenport and Prusak, 1998
I often publish and share my own professional resources on Moments (or directly communicate with friends) of WeChat.
I like to post my personal feelings or ideas on Moments of WeChat.
Replies I usually participate in interaction (in chat groups or Moments) during discussing about complex issues. Xu, M and Ye, 2011; Hsu, Ju, Yen, and Chang, 2007; Davenport and Prusak, 1998
I often discuss to a variety of topics rather than a specific topic with friends.
I am often attracted by statements (text or pictures) released by friends, and then participate in the discussion.
Generalized trust Affective trust I can freely share my ideas, feelings, and thoughts on WeChat (such as Moments, WeChat group). Chang and Chuang, 2011; Chiu, Hsu, and Wang, 2006; Lewis and Weigert, 1985
I can optionally discuss difficulties encountered in study or work on WeChat (such as Moments, WeChat group).
When I send difficulties confused me in WeChat group (or communicate directly with WeChat friends), or post on Moments, they will give some constructive suggestion.
In exchanges of information on WeChat (such as Moments, WeChat group), I always care about that interests of the other party are not damaged.
Friends and I do our utmost to establish and maintain good information interaction on WeChat.
Cognitive trust Friends have strong abilities of peer communication on my WeChat (such as Moments, WeChat group). Chang and Chuang, 2011; Chiu, Hsu, and Wang, 2006; Lewis and Weigert, 1985
Friends never make fun of or take advantage of others' weaknesses on my WeChat (such as Moments, WeChat group).
Friends would unreservedly share personal experience and knowledge with me on my WeChat such as Moments, WeChat group).
My WeChat friends would not reveal information we exchanged to others at random.
Personality traits Agreeableness The regularity and forms of both nature and art make me feel very mysterious. McCrae and Costa, 1997; Costa and McCrae, 1992
I like thinking and playing with theory or abstract concept.
I'm good at finding differences of objects from another side
I'm full of curiosity about idealistic things.
Conscientiousness I am efficient and capable on my job. McCrae and Costa, 1997; Costa and McCrae, 1992
I will keep my belongings neat and clean
I will do my best to finish my assigned work
I do not easily make a promise. Once I did, I would carry out it to the end