"I'll poke you. You'll poke me!" Self-disclosure, social attraction, predictability and trust as important predictors of Facebook relationshipsPavica Sheldon
Louisiana State University, USA
Keywords: Facebook, social network sites, structural equation modeling, friendship, uncertainty reduction theory
It is not news that personal relationships are forming online as well as offline. Personal relationships can also be maintained online, such that senders and receivers do not have to look at each other face-to-face. Although online communication can lack face-to-face characteristics, such as physical proximity, frequent interaction, and physical appearance, people in an online setting can still reduce their uncertainty about one another. According to researchers, (Bargh, McKenna, & Fitzsimons, 2002; McKenna, Green, & Gleason, 2002; Wellman & Gulia, 1999), frequency of contact is what is crucial in the formulation of online relationships. Physical proximity is not possible. According to Walther (1996), computer-mediated communication facilitated the formation of “hyperpersonal” relationships – greater feelings of intimacy than would have otherwise been experienced in face-to-face (FTF) relationships.
Due to the growth of new social software applications such as Instant Messaging, Blogs, Wikis, and a variety of social network services, today people connect and interact through computer-mediated communication (Gennaro & Dutton, 2007), of which Facebook and MySpace are most popular. The main motive for Facebook use in studies by Ellison, Steinfield and Lampe (2007) and Sheldon (2008) is relationship maintenance or social contact with people we know in real life. Founded in 2004 by Harvard undergraduate student Mark Zuckerberg, Facebook is one of the fastest growing social network sites (SNS) today, with over 300 million active users (http://www.facebook.com, October, 2009), of which the majority are college students (Mack, Behler, Roberts, & Rimland, 2007). The generation born roughly between 1980 and 1994 has been characterized as the “digital natives” (Prensky, 2001) or the “Net generation” (Tapscott, 1998). They are living lives immersed in technology, “surrounded by and using computers, videogames, digital music players, video cams, cell phones, and all the other toys and tools of the digital age” (Prensky, 2001, p. 1). Arnett (2004) coined the term “emerging adulthood” to describe young adults (between the ages of 18 and 29) who are postponing marriages and parenthood until their late twenties and later, while spending their time in self-focused exploration, searching for their career and religious identities (Cote, 2006). Arnett (2004) argued that emerging adulthood is “a time of exploration and instability, a self-focused age, and an age of possibilities” (p. 21). Acar (2008) argued that online social networks, better known as social network sites (SNS), are not only larger than regular social networks but also structurally different since they are not highly influenced by demographic factors such as income and attractiveness. An average Facebook user has several times more friends on Facebook than in real life (Acar, 2008; Sheldon, 2008), the reasons being a perceived lower risk of accepting new members, easiness of requesting a membership, social desirability (positive feeling of online popularity), and failing to exclude members who are no longer contacted (Acar, 2008, p. 77).
A January 2009 Compete.com study has ranked Facebook as the most used social network by worldwide monthly active users, followed by MySpace (Kazeniac, 2009). Its “Top Friends” application was the most engaged application among U.S. Internet users in November 2007. According to the same source, visitors between the ages of 18-24 were twice as likely as the average Facebook visitor to engage with applications, while those aged 25 and older were less likely than average to exhibit this behavior (comScore.com, 2008).
Previous research found that university students go to Facebook to maintain their relationships (Ellison et al., 2007; Sheldon, 2008), pass time when bored, or to find companionship (Sheldon, 2008). Within and across social networks, users are allowed to search for other registered users and can initiate requests to other individuals to be friends. The implicit definition of friends on Facebook ranges from established intimate relationships to simply being acquainted (boyd, 2006).Boyd (2008) argues that SNSs are “network publics” that support sociability, just as unmediated public spaces do.
Emerging adults use a variety of online and offline social networks to establish intimacy and connect and reconnect with friends and family members (Subrahmanyam, Reich, Waechter, & Espinoza, 2008). In a Subrahmanyam et al. (2008) study, emerging adults used social network sites to stay in touch with their friends and relatives that they have not seen that often. Most of their time on social networking sites was spent reading comments, writing comments, and responding to comments and messages. In the Subrahmanyam et al. study, college students answered the questions about their closest friend in three contexts: social networking sites, instant messaging, and face-to-face. Although studies (Steinfield, Ellison, & Lampe, 2008) suggested that emerging adults use social networking sites to connect with people from their offline lives, the overlap between the mediums in the Subrahmanyam et al. study was not perfect. In fact, only slightly more than half had any overlap between their top instant messaging, social networking, and face-to-face friends. Few (2.5%) had a perfect overlap between their online and offline friends. This suggests that young adults’ offline and online worlds are not mirror images of each other (Subrahmanyam et al., 2008).
Researchers have also been interested in who benefits from online relationships. The Social Compensation or “Poor-Get-Richer” Hypothesis suggests that those who have poor social networks and social anxiety can get more benefit by disclosing themselves freely and creating new relationships through the Internet. Internet benefits introverts more than extraverts (McKenna & Bargh, 2000). That is, new relationships and interactions online may compensate for the social capital that these people lack in the offline world. Studies showed that the Internet’s anonymity and reduced cues might stimulate online self-disclosure because there is no fear of being ridiculed or rejected (Derlega, Metts, & Petronio, 1993; Pennebaker, 1989). Sheldon and Honeycutt (2008) found that students who are afraid of face-to-face meetings are more likely to go on Facebook to pass time when bored or to occupy their time. On Facebook they can interact with others without looking at each other’s face. This may be particularly appealing to introverts when trying to open up.
On another hand, scholars (Kraut, Kiesler, Boneva, Cummings, Helgeson, & Crawford, 2002) argued that the “Rich-Get-Richer” hypothesis may be true. The “Rich-Get-Richer” or the Social Enhancement Hypothesis states that the Internet primarily benefits extraverted individuals. Peter, Valkenburg, and Schouten (2005) found that extraverted adolescents self-disclosed and communicated online more often. Moreover, MacIntyre, Babin, and Clement (1999) found that extroverts communicate more with others on the Internet than do introverts. Online communication, according to them, increases the opportunities for extraverted adolescents to make friends. In their model, extraverted individuals disclosed more online than introverted.
The reason for such contradictory findings is not by chance. Online communities such as chats, blogs and social networks have different purposes, and therefore attract different audiences. Facebook is a social network that connects people that know or knew each other face-to-face. In fact, Sheldon (2008) reports that individuals who feel anxiety and fears in their face-to-face communication use Facebook to pass time and feel less lonely more often than other respondents, but they have fewer Facebook friends. Her findings support the Rich-Get-Richer Hypothesis (Kraut et al., 2002). People who get involved in online relationships are not necessarily those with difficulties in face-to-face communication. Facebook resembles word-of-mouth communication.
Studies have also compared the qualities of online versus offline relationships. While some studies suggested that features of online communication, such as anonymity and isolation make it easier for individuals to form strong ties (McKenna et al., 2002; Joinson, 2001), other reported that that the quality of online social interactions is lower than that of face-to-face interactions (Haythornthwaite, 2002). In one study, college students evaluated e-mail communication as inferior to communication in person (Cummings, Butler, & Kraut, 2002). Wellman (1997), however, noted that the relationships formed online are strong when they are voluntary and revolve around a common interest. Social Information Processing Theory (SIPT; Walther, 1992) has been developed to explain how people develop and maintain relationships in a computer-mediated environment. According to SIPT, people can develop online relationships that are similar to or better than normative face-to-face interactions. Even when nonverbal cues are unavailable, the remaining communication systems are employed to do the work of those that are missing (Walther, 2008). The theory asserts that, when individuals are motivated and allowed sufficient time to exchange social information, relationships developed via CMC approximate to the same level of development over time as those established through face-to-face interaction (Walther & Burgoon, 1992; Walther, 1996).
Numerous studies have been conducted in the area of interpersonal relationships to describe how friendships develop (Chan & Cheng, 2004). According to Parks and Floyd (1996) and Chung (2003), interpersonal relationships of all types are usually conceptualized as developing from the impersonal to the personal along a series of relatively specific dimensions: an increase in interdependence, breadth and depth of the interaction, a shared communicative code change (specialized ways of communicating), an interpersonal predictability and understanding, and a continued relationship into the future. Uncertainty Reduction Theory and Social Penetration Theory can potentially improve understanding of the development and qualities of computer-mediated relationships.
A number of studies have looked at how people use Facebook and MySpace, but few (Craig, Igiel, Wright, Cunningham, & Ploeger, 2007) have concentrated on testing existing interpersonal communication and relationship theories in a social network setting. Craig et al. (2007) examined the role of perceived similarity and social attraction on self-disclosure on Facebook, and they found that CMC relational development and face-to-face relational development are quite similar. The perception of attraction influenced self-disclosure patterns. Since some findings (Walther, 1992, 1996) on FTF relationship development suggests that self-disclosure drives attraction, Craig et al. (2007) proposed to explore the possibility of that relationship. They also urged for the expansion of the model so it includes other variables.
In order for online communities to survive, it is important that people trust each other. Trust is a key component of any healthy relationship. Although it has not been extensively studied in CMC, trust is important for the development of intimacy and commitment (Anderson & Emmers-Sommer, 2006) and for the development of close relationships (Rempel, Holmes, & Zanna, 1985). According to Rempel et al. “trust is seen to evolve out of past experience and prior interaction; thus it develops as the relationship matures” (p. 96).
The present study explores relationship development on Facebook by focusing on the relationship between social attraction, self-disclosure, predictability, and trust between Facebook users. As advised by Craig et al. (2007), we tested two models, one in which social attraction drives self-disclosure and one in which self disclosure leads to a higher level of interpersonal trust in the person to whom we disclose. The second model tested the hypothesis that self-disclosure leads to interpersonal attraction and is an outcome of trust. Predictability was a mediating variable between self-disclosure and trust in both models. Since we had multiple dependent relationships, Structural Equation Modeling (SEM) was used to test our research questions. The overarching goal of this study was to advance the understanding of Social Penetration Theory and Uncertainty Reduction Theory in a computer-mediated environment, specifically in a Facebook relationship. Members of Facebook disclose lots of private information online.
They display not only their personal interests, but also pictures of themselves, which may influence perceptions of their physical and social attractiveness. Within a face-to-face context, many relational development studies posit that increases in self-disclosure lead to perceptions of interpersonal attractions. We discuss what the self-disclosure is and how it is related to social attraction.
Self-Disclosure and Interpersonal Attraction on Facebook
Self-disclosure is the process of revealing personal information about oneself verbally (e.g. Berg & Derlega, 1987). Personal information refers to private information than cannot be obtained without importing other direct or indirect methods (e.g. Kim, Lee, & Park, 2006; Derlega et al., 1993). In interpersonal relationships, self-disclosure plays a crucial role in the development of human relationships. Self-disclosure can also be a strategy for impression formation, social validation, or social control (Kim, Lee, & Park, 2006; Derlega et al, 1993). A theory that deals with the different aspects of self-disclosure in relationship development is called the Social Penetration Theory. According to Social Penetration Theory (Altman & Taylor, 1987), relationships develop as the level of social penetration increases. Altman and Taylor (1973) dimensions of self-disclosure include: a) breadth, the amount of information, or number of topics of self-disclosure, and b) depth, the intimacy of self-disclosure. Studies usually show that the level of intimacy has a much larger effect than the amount disclosed in the disclosure-liking framework (Kim, Lee, & Park, 2006; Collins & Miller, 1994).
SPT had been applied to the computer-mediated communication context. Tidwell and Walther (2002) found that people who display interest through CMC produce significantly higher proportions of self-disclosures than did those in FTF interactions. Also, CMC dyads compensated for the limitations of the channel by making their questions more intimate than those who exhibited face-to-face. According To Walther’s (1996) hyperpersonal communication framework, the reduced nonverbal cues of CMC encourage people to feel less inhibited and more likely to disclose their inner feelings at an earlier stage (1996).
Two different groups of theorists have suggested that self-disclosure is related to interpersonal attraction. According to one group of researchers (Walther & Burgoon, 1992; Tidwell & Walther, 2002) who studied the relationship between impression formation (including attraction) and self-disclosure in a computer-mediated environment, greater self-disclosure online leads to perceptions of interpersonal attraction. Self-disclosure provokes attraction (Derlega et al., 1993; McAllister & Bregman, 1983). Other CMC studies (Ramirez, Walther, Burgoon, & Sunnafrank, 2002; Levine, 2000) support the idea that perceptions of attraction may drive self-disclosure. People tend to like those who disclose to you first, and people tend to disclose more to those they like (Collins & Miller, 1994; Kim, Lee, & Park, 2006). According to Theorem 14 of Uncertainty Reduction Theory, persons tend to disclose intimate information to persons they like and withhold intimate information from persons whom they do not like (Berger & Calabrese, 1975).
Since researchers cannot agree about causal relationships between self-disclosure and social attraction, we ask the following research question in relation to Facebook relationships:
RQ1: What is the relationship between social attraction and self-disclosure in Facebook relationships?
Uncertainty Reduction Theory
Initially, Berger and Calabrese (1975) developed Uncertainty Reduction Theory (URT) to explain only initial interactions between people. Later, Berger (1987) updated the theory. He argues that uncertainties are ongoing in relationships and are not just relevant to initial interactions. Parks and Adelman (1983) found that the more partners communicate with their social networks (friends and family members), the less uncertainty that they will experience. Furthermore, the researchers found that the less uncertainty people feel, the less likely they will be to dissolve a relationship with another.
Axiom 1 of URT states that “given the high level of uncertainty present at the onset of the entry phase, as the amount of verbal communication between strangers increases, the level of uncertainty for each interactant in the relationship will decrease. As uncertainty is further reduced, the amount of verbal communication will increase” (Berger & Calabrese, 1975, p. 102). This means that both persons have to verbally communicate in order to reduce uncertainty or increase predictability about each other. More verbal communication means easier prediction of another person’s behavior, which in turn means more verbal communication since a person can predict another’s reaction. The reduction of uncertainty helps users decide if they want to initiate a relationship with the other person; similarities between the two users should decrease uncertainty, and the decrease in uncertainty should subsequently increase liking (Berger & Calabrese, 1975).
Although online communication can lack face-to-face characteristics, such as physical proximity, frequent interaction and physical appearance, people in an online setting can still reduce their uncertainty about one another. None of the theories of relational development, according to Parks and Floyd, requires physical proximity and frequent interaction for relational development. They may be helpful, but they are not necessary for reducing uncertainty or the reward/cost ratio. Walther (1992) suggested that without nonverbal cues, communicators adapt their relationship behaviors to the remaining cues available in CMC, such as content and linguistic strategies, as well as chronemic and typographic cues (Walther & Tidwell, 1995). Park, Jin and Jin (2009) also argued that individuals’ strategies to reduce uncertainties in face-to-face interaction can be applied in computer-mediated settings such as social network sites as well. However, many Facebook relationships are already existing face-to-face relationships and self-disclosure has already occurred. Therefore, we speculate that the predictability should be high.
Self-Disclosure, Predictability and Trust
Self-disclosure facilitates developing close relationships and mutual trust (Altman & Taylor, 1973). Trust has not been extensively studied in a computer-mediated environment though it is associated with self-disclosure in face-to-face interactions (Kim, Lee, & Park, 2006). A survey of individuals in exclusively online romantic relationships found that both the length of time the relationships had lasted, as well as the amount of time spent communicating with one’s partner, were significantly associated with perceived attitude similarity, commitment, intimacy, and trust (Anderson & Emmers-Sommer, 2006). Wheeless and Grotz (1977) found a positive correlation between trust and the amount, depth, and honesty of self-disclosure. Meeting face-to-face prior to communicating online helps to promote trust (Zheng et al., 2002). Research has also shown that those who are more trusting in real life have a harder time trusting online (Feng, Lazar, & Preece, 2004). However, as Kim, Lee and Park (2006) discussed, trust does not increase linearly with the increase in self-disclosure. The most important element in developing trust about another is the overall predictability of that individual (Rempel, Holmes, & Zanna, 1985). According to the Rempel et al. model, predictability is actually one of the dimensions of trust. We self-disclose to a person if we can predict their behavior. Prediction is the ability to forecast one’s own and others’ behavioral choices. Therefore, we speculate that the predictability of another person’s behavior will be a mediator between self-disclosure and trust in Facebook relationships.
H1: Predictability will mediate the relationship between self-disclosure and trust in Facebook relationships.
Again, since researchers cannot agree about the relationship between self-disclosure and trust, we posited a research question:
RQ2: How is self-disclosure on Facebook related to interpersonal trust that we feel toward the person to whom we disclose on Facebook?
In order to test the hypothesis and research questions, we employed confirmatory factor analysis (CFA) and structural equation modeling (SEM). The first model tested earlier findings that attraction drives self-disclosure (Ramirez et al., 2002; Collins & Miller, 1994; Kim, Lee, & Park, 2006) and self disclosure leads to a higher level of interpersonal trust in the person that we disclose to. The second model tested the hypothesis that self-disclosure leads to interpersonal attraction (Tidwell, & Walther, 2002; Derlega et al., 1993; McAllister & Bregman, 1983), and self-disclosure is an outcome of trust. We have also included predictability as a mediator variable in each model.
The participants were 243 undergraduate students enrolled in introductory communication courses at Louisiana State University in Baton Rouge, USA. The participants represented various academic disciplines. The sample consisted of 120 (49%) men and 123 (51%) women with an average age of 20 (ranging from 18 to 36 years). The largest number of participants were sophomores (36%) and Caucasians (91%).
Procedures and Measurement
The pre-condition to participate in the paper-pencil survey was to be an active Facebook user. Participation was voluntarily and students received extra credit. Previously, a small group of seven college students filled out a pre-test questionnaire to check for the face and content validity. Most measures were Likert scales, and reliabilities are reported as Cronbach’s alpha. The study was approved by the Institutional Review Board at Louisiana State University.
Students were asked to report how many close friends they have and what modes of communication they use (face-to-face, email, MSN chat, ICQ, Skype, Facebook, Cell phone/Text messaging) on a 7-point scale where 7 represents “regular” use, and 1 “never use”. We asked how many Facebook friends they have and how many hours they spend on Facebook on an average day. We asked them a variety of well-established instruments to measure social attraction, breadth and depth of self-disclosure, predictability, and interpersonal trust in an individual they disclose most on Facebook.
Social attraction. Social attraction towards the individual was measured using the “social attraction” component of McCroskey and McCain (1974) Interpersonal Attraction Scale (IAS). A number of researchers have reported high internal reliability coefficients for various dimensions (Ayres, 1989; Brandt, 1979; Krikorian, Lee, Chock, Harms, 2000; McCroskey & McCain, 1974; Wheeless, Frymier, & Thompson, 1992). Respondents answered six questions (i.e. “He/she just wouldn’t fit into my circle of friends,” “I think he/she could be a friend of mine”) on a 5-point Likert-type scale (5 = strongly agree, and 1 = strongly disagree). The items measured respondents’ social attraction to one individual that they talked with the most on Facebook. The Cronbach’s alpha reliability coefficient for this measure was .76 (M = 4.42, SD = .62).
Self-disclosure. Self-disclosure to a Facebook and face-to-face friend was measured by Parks & Floyd’s (1996) scale that is developed based on Altman and Taylor’s (1973) scales of self-disclosure, measuring depth and breadth. Although other scales exist (e.g., Joinson, 2001; Wheeless & Grotz, 1976) to measure self-disclosure in both an online and offline environment, we have used the Parks and Floyd (1996) breadth and depth scale because it captures disclosure to another person more directly than the Wheeless and Grotz (1976) study. The Parks and Floyd (1996) scale is also topic-free and was used in numerous studies (e.g., Craig et al., 2007; Yum & Hara, 2005) to measure self-disclosure online.
Participants were asked to complete these items based on their interactions with one individual they talked with the most on Facebook. Both measures use a five-point Likert-type scale, and they were originally developed to measure self disclosure online (Craig et al, 2007). The breadth measure consisted of five items, and it was used to assess the range of topics partners discussed in these relationships (i.e. “Our communication ranges over a wide variety of topics,” “Our communication covers issues that go well beyond the topic of any one particular application”). The depth measure contained eight items, including: “I usually tell this person exactly how I feel,” and “I feel quite close to this person.” The Cronbach’s alpha coefficient for this instrument was .82 for depth (M = 3.77, SD = .75) and .83 for breadth (M = 4.00, SD = .80).
Predictability. Perceptions of predictability and understanding are important aspects of Uncertainty Reduction Theory (Berger & Calabrese, 1975; Parks & Adelman, 1983). We examined these perceptions using Parks and Floyd’s scale (1996) (e.g., “I am very uncertain about what this person is really like,”) that measures predictability of an online friend’s behavior. To assess predictability five items were used, and they included statements such as, “I am very uncertain about what this person is really like,” and “I can usually tell what this person is feeling inside.” Responses were measured on a five-point Likert type scale where 5 = strongly agree, and 1 = strongly disagree. The Cronbach’s alpha reliability coefficient for this measure was .79 (M = 3.95, SD = .82). Two items were reversely coded.
Trust. Interpersonal trust was measured using the Individualized Trust Scale (Wheeless & Grotz, 1977), which is a 7-point semantic differential scale. The scale assesses the perception of individuals by showing them pairs of adjectives: trustworthy-untrustworthy, deceptive-candid, confidential-divulging, exploitive-benevolent, safe-dangerous, not deceitful-deceitful, tricky-straightforward, respectful-disrespectful, inconsiderate-considerate, honest-dishonest, unreliable-reliable, faithful-unfaithful, insincere-sincere, and careful-careless (M = 5.69, SD = .98, Cronbach’s alpha = .92).
On average, students reported having 455 Facebook friends, which is actually a minimum number since most students wrote “at least” and then a certain number of friends. The maximum number of Facebook friends was 2,000 and the minimum 4. Students said they had 7 “close” friends on average. Interestingly they report communicating with their close friends through cell phone most often (on a scale from 1-7, 7 being a ‘regular’ mode of communication, M = 6.48, SD = .88), following by face-to-face conversations (M = 6.11, SD = 1.39), Facebook (M = 4.08, SD = 1.85), e-mail (M = 2.21, SD = 1.41) and lastly IM use (M = 2.07, SD = 1.68). On average, students spend 60 minutes per day on Facebook (M = 59. 95, SD = 55. 28). The exploratory data analysis revealed a positively skewed, leptokurtic distribution (Shapiro-Wilk's = .86, p = .000; kurtosis = 2.26; skewness = 1.41). This, however, will not influence our data analysis as we use these variables for informative purposes only.
Prior to testing the relationship between social attraction, self-disclosure, predictability and trust, we conducted an exploratory factor analysis to see how the items load on these four constructs. The results of the exploratory factor analysis (EFA) showed that some factors loaded poorly on the trust and depth dimension of self-disclosure and were removed from the model.
A structural equation modeling (SEM) analysis of 213 subjects was undertaken using the AMOS 16.0. SEM was selected as a statistical methodology because of its several advantages over regression modeling, including its more flexible assumptions (particularly allowing interpretation even in the face of multicollinearity), use of confirmatory factor analysis to reduce the measurement error by having multiple indicators per latent variable, better model visualization, the desirability of testing models overall rather than coefficients individually, the ability to test models with multiple dependents, the ability to model mediating variables, the ability to test coefficients across multiple between-subjects groups, and ability to handle difficult data (non-normal data, incomplete data) (Garson, 2009).
Testing the measurement model
We conducted a confirmatory factor analysis (CFA) with four variables (self-disclosure, social attraction, predictability, and trust). Although the EFA gives an idea of dimensionality, CFA, as the name implies, essentially focuses on whether a hypothesized factor model does or does not fit the data. Thus, CFA is a commonly accepted method to test/confirm dimensionality (Netemeyer, Bearden, & Sharma, 2003). Because there is no single universally accepted fit index, a variety of indices were used to provide a comprehensive indication of fit.
First, the chi-square test was conducted to test the fit between the sample covariance matrix and the matrix implied by the models. A large chi-square value and a statistically significant result (i.e., p < .05) indicate a poor fit in that there is a substantial proportion of variance in the data not explained by the model. As this statistic is somewhat sensitive to sample size, a second calculation can be made that involves dividing the chi-square value by the degrees of freedom (Kline, 1998). Although no clear-cut guideline exists, a ratio below 3 is generally considered to be acceptable (Kline, 1998). Fit statistics insensitive to sample size were also used, including the goodness-of-fit index. One badness-of-fit measure (root mean square error of approximation) was used. Values below .08 for RMSEA are generally considered to be acceptable.
The overall fit of the measurement model was good (chi-square/df = 1.57, CFI = .94, TLI = .93, RMSEA = .06) and all correlations were significant. Items showed convergent validity (loadings higher than .5, AVE higher than .5, construct reliability larger than .7). The next step was to determine the discriminant validity. Discriminant validity compares the variance extracted estimates (AVE) from each factor with the squared interconstruct correlations (SIC) associated with that factor. Comparing the AVE and interconstruct correlations, we found evidence that all factors had discriminant validity.
Our RQ1 asked how much the perception of attraction influences self-disclosure and how much the self-disclosure influences attraction. In a first model, social attraction influences self-disclosure, and self-disclosure leads to a greater predictability and trust. Breadth influences the depth of self-disclosure (Altman & Taylor, 1987). We tested what Craig et al. (2007), Kim, Lee and Park (2006), and Ramirez et al. (2002) would have suggested. Again, we employed AMOS 16.0, a covariance-based tool. Results (Figure 1) showed a good model fit.
The Chi-square/df ratio was 1.56. For a model with a good fit, most empirical analyses suggest that the ratio of chi-square normalized to the degree of freedom should not exceed 3.0 (Tabachnick & Fidell, 1996). In addition, the comparative fit index (CFI) was .94, and the Tucker-Lewis (TLI) index was .93. The indices were well above the .90 benchmark (Hair, Black, Babin, Anderson, & Tatham, 1998). The Root Mean Square Error of Approximation (RMSEA) was .06. In the case of RMSEA, values less than .05 indicate a good fit, values as high as .08 represent reasonable, and values ranging from .08 to .10 indicate a mediocre fit (Byrne, 2001). Therefore, the results indicate the hypothesized model was a good fit. Table 1 represents the significance of path coefficients for all variables in the model. All paths were significant (p < .05). However, our goal was to examine the strength of the relationships between social attraction, self-disclosure, predictability and trust, so we could compare them with model 2 in which self-disclosure leads to social attraction.
Table 1 depicts very interesting findings related to the influence of social attraction on self-disclosure, predictability and trust. A very strong relationship (β = .80) was found between the depth dimension of self-disclosure and predictability, which suggests that revealing private information about ourselves to another Facebook friend is strongly related to a high certainty about another person (how he/she feels/acts). The more information one gets about another person, the less uncertainty he or she has. A weak relationship (β = .18) existed between the idea that the perceptions of social attraction may drive the intimacy of self-disclosure. However, breadth, or the number of topics one discusses on Facebook, was moderately related to the perception of social attraction (β = .35). We found no significant relationship between predictability and trust, which would suggest that the predictability of someone’s behavior does not lead us to trust that person more.
However, we wanted to know if predictability is a mediator between self-disclosure and the trust one has in a Facebook friend, as literature suggests, and how in that case the relationship between predictability and trust would change. As Figure 2 shows, we made predictability a mediator between the depth of self-disclosure and trust. The new model fit the data, and its fit indices were very similar to those in the model when predictability was not a mediator between self-disclosure and trust. However, in this case, the relationship between predictability and trust was also significant, so we can conclude that the mediating model (Figure 3) better explains our data. Our hypothesis that predictability is a mediator between the intimacy of self-disclosure and trust is therefore supported.
In the second model, we tested self-disclosure’s influence on social attraction and trust’s influence on self-disclosure. We tested what Tidwell and Walther (2002), Derlega et al (1993), and McAllister and Bregman (1983) suggested. Our model showed a good fit (Figure 3).
The Chi-square/df ratio was 1.86. In addition, the comparative fit index (CFI) was .91, and the Tucker-Lewis Index (TLI) was .89. The Root Mean Square Error of Approximation (RMSEA) was .076. All paths were significant (Table 2), except the path between the breadth of self-disclosure and social attraction. This suggests that the range of topics that we discuss with another person does not necessarily lead to our perception that this other person is socially more attractive. However, as we found in model 1, we discuss a wide range of topics on Facebook with someone we find socially attractive. Self-disclosure may provoke the social attraction to a greater degree (β = .30) than the social attraction drives self-disclosure (β = .18) (in model 1). In addition people tend to disclose to trusted people and those whose behavior they can predict. The stronger relationship between self-disclosure, predictability and trust was, however, found in model 1, which can better explain the relationship between attraction, self-disclosure, predictability and trust.
Again, we wanted to know if predictability mediates the relationship between self-disclosure and trust. The mediating model actually showed a similar fit to the nonmediated, and all paths were significant. In this case, predictability again proved to mediate the relationship between the depth of self-disclosure and trust ( Χ2 (243)/df=1.89, CFI=.90, TLI=.89, RMSEA = .077).
Relationships develop online the same as they do offline. The appearance of social network sites, such as Facebook.com and MySpace.com, offer new opportunities for people to socialize, self-disclose and reduce uncertainties about one another. It also offers a new possibility for communication researchers to test how interpersonal communication theories work in a new setting. Walther (1994) found that when controlling for anticipated interaction, CMC relational development and face-to-face relational development are quite similar. Craig et al. (2007) examined the role of perceived similarity and social attraction on self-disclosure on Facebook and found that perception of attraction influenced self-disclosure patterns. Since some findings (Derlega et al., 1993; McAllister, & Bregman, 1983) on face-to-face relationship development and CMC relationship development (Walther, 1992; 1996) suggest that self-disclosure drives attraction, Craig et al. (2007) proposed to explore the possibility of a reverse relationship between these variables in a CMC setting. They also urged for the expansion of the model so that it includes other variables.
The purpose of this research was to test how one Facebook user’s social attraction influences another person’s self-disclosure and perception of trust in that individual. Our research was inspired by a Craig et al. (2007) study, and we expanded their model by adding predictability as a mediating variable between self-disclosure and trust.
We tested two models. The first model supports findings that the perception of attraction drives self-disclosure (Craig et al., 2007; Kim, Lee, & Park, 2006; Ramirez et al., 2002; Collins & Miller, 1994), especially the number of topics we discuss with somebody on Facebook. Self-disclosure also leads to higher levels of interpersonal trust in the person we disclose to. The second model finds support that greater self-disclosure leads to the perception of interpersonal attraction (Tidwell, & Walther, 2002; Derlega et al., 1993; McAllister, & Bregman, 1983), but only if the topics disclosed are intimate. Our first model (Figures 2 and 3) fits data much better than the second model (Figures 4 and 5).
The relationship between the depth of self-disclosure or the intimacy of self-disclosure and trust is actually mediated by predictability. In the first model, predictability fully mediates the relationship between self-disclosure and trust. This supports Uncertainty Reduction Theory, which suggests that the more we disclose, the less uncertainty that we feel toward the individual.
Although the path coefficients between social attraction and the depth of self-disclosure are significant in both models, as our results suggest, the depth of self-disclosure or the intimacy of the information that we reveal to our Facebook friend can provoke social attraction to a greater degree than social attraction can the depth of self-disclosure. This means that on Facebook we tend to like people to whom we self-disclose our intimate information. The key, however, is not in the quantity of self-disclosure (breadth) that makes us like our Facebook friends, but in the quality (depth). We tell our personal secrets to those that we like. The key seems to be in the intimacy of self-disclosure, the quality and not the quantity. This supports Altman and Taylor (1973) and Social Penetration Theory, which suggest that changes in the outer layer (breadth) minimally change the relationships.
Our findings thus support researchers (Ramirez et al., 2002; Collins & Miller, 1994; Kim, Lee , & Park, 2006) who claimed that perceptions of attraction drive self-disclosure and partially supports researchers (Tidwell & Walther, 2002; Derlega et al., 1993; McAllister & Bregman, 1983) that say greater self-disclosure leads to perceptions of interpersonal attraction.
We have also found a significant relationship between the depth of self-disclosure, predictability of another person’s behavior and trust in that individual. Although many nonverbal cues are absent on Facebook, its users still perceive a high predictability of their Facebook friends’ behavior. The reason may be the fact that Facebook relationships are usually existing face-to-face relationships and self-disclosure has already occurred. Facebook users have very little uncertainty about the behavior of the person to whom they intimately self-disclose to. They self-disclose to persons that they can predict the thoughts, feelings, or behaviors of. This leads to trust in that individual. People tend to disclose to trusted partners. All this supports Uncertainty Reduction Theory that was developed to explain the uncertainty reduction in face-to-face relationships. “As the amount of verbal communication between strangers increases, the level of uncertainty for each interactant in the relationship will decrease. As uncertainty is further reduced, the amount of verbal communication will increase” (Berger & Calabrese, 1975, p. 102).
By disclosing on Facebook, users not only find other individuals socially more attractive, but they can predict their attitudes, values, and beliefs. Predictability is one of the basic premises of Uncertainty Reduction Theory. Predictability is related to uncertainty in both Facebook and in a face-to-face context, and the more uncertainty that existed in the relationship, the less trust also existed. This supports Dainton and Aylor ( 2001) who found support for trust as “a potent means for reducing relational uncertainty” (p. 183). Walther (1996) also found that the CMC relational development and face-to-face relational development are quite similar. Individuals, as do Facebook users, adapt their communication behavior in limited-cue environments, utilizing whatever mechanisms are available for gathering information and reducing uncertainty about partners (Tidwell & Walther, 2002). Our findings support Uncertainty Reduction Theory – the more Facebook users talk, the less uncertainty they experience (Axiom 1) and are able to like each other more (Axiom 7).
However, not all online communities resemble Facebook features. Future researchers should examine the same models in different online contexts. They could test the same models in a face-to-face context and compare how relationships develop when nonverbal cues are present. We could also test if there are cultural differences in self-disclosure: how much do the members of individualistic cultures (such as the United States) disclose on Facebook versus the members of collectivistic cultures (e.g. China). According to Yum and Hara (2006), self-disclosure in individualistic cultures is seen as more positive, reduces uncertainty about others and increases interpersonal trust. For Koreans, self-disclosure was inversely associated with trust, whereas it was a non-factor for the Japanese. Are Social Penetration Theory and Uncertainty Reduction Theory culturally specific? Years ago it was noted that research on new technology was “data rich but theory poor” (Steinfield & Fulk, 1990, p.13), and this statement holds true with respect to research on online communities and social networks today.
This study has several limitations. First, we used a convenient sample that consisted of students who were enrolled in communication classes. Second, we collected data on students asking them to think about the Facebook friend that they talk to most often on Facebook. We can not generalize our findings and claim that their social attraction to a Facebook friend is a result of their self-disclosure on Facebook. Our SEM model can only point in that direction. The same relationships should be tested in a different environment, while controlling for other variables that might influence the relationships between variables. Longitudinal studies should be conducted to establish a causal relationship between social attraction and self-disclosure, self-disclosure and predictability, and predictability and trust. However, our study brings some new insights into how traditional communication theories, such as Social Penetration Theory and Uncertainty Reduction Theory, could be applied in a computer-mediated setting. It also suggests that we should integrate new theories, such as Social Processing Information, into our studies in order to get a better picture of interactions through social networking sites.
Acar, A. (2008). Antecedents and consequences of online social networking behavior: The case of Facebook. Journal of Website Promotion, 3, 62-83.
Altman, I., & Taylor, D. (1973). Social penetration: The development of interpersonal relationships. New York: Holt, Rinehart, & Winstron.
Anderson, T. A., & Emmers-Sommer, T. M. (2006). Predictors of relationship satisfaction in online romantic relationships. Communication Studies, 57, 153-172.
Arnett, J. J. (2004). Emerging adulthood: The winding road from the late teens through the twenties. New York: Oxford University Press.
Ayres, J. (1989). The impact of communication apprehension and interaction structure on initial interactions. Communication Monographs, 56, 75-88.
Bargh, J. A., McKenna, K. Y. A., & Fitzsimons, G. M. (2002). Can you see the real me? Activation and expression of the “true self” on the Internet. Journal of Social Issues, 58, 33-48.
Bargh, J. A. & McKenna, K. Y. A. (2004). The Internet and social life. Annual Review of Psychology, 55, 573–590.
Berg, J. H., & Derlega, V. J. (1987). Themes in the study of self-disclosure. In V. J. Derlega, & J. H. Berg (Eds.), Self-disclosure: Theory, research, and therapy (pp. 1-8). New York: Plenum Press.
Berger, C. R. (1987). Communicating under uncertainty. In M. E. Roloff & G. R. Miller (Eds.), Interpersonal processes (pp. 39-62). Newbury Park, CA: Sage.
Berger, C. R., & Calabrese, R. J. (1975). Some explorations in initial interaction and beyond: Toward a developmental theory of interpersonal communication. Human Communication Research, 1, 99-112.
boyd, d. (2006). Friends, friendsters, and top 8: Writing community into being on social network sites. First Monday, 11(12). Retrieved July 1, 2007, from http://firstmonday.org/issue/....
boyd, d. (2008). Why youth (heart) social network sites: The role of networked publics in teenage social life. In D. Buckingham (Ed.), Youth, Identity, and Digital Media (pp. 119 – 142). Cambridge, MA: MIT Press.
Brandt, D. R. (1979). On linking social performance with social competence: Some relations between communication style and attributions of interpersonal attractiveness and effectiveness. Human Communication Research, 5, 223-237.
Byrne, B. M. (2001). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Mahwah, NJ: LEA.
Chan, D. K.-S., & Cheng, G. H.-L. (2004). A comparison of offline and online friendship qualities at different stages of relationship development. Journal of Social and Personal Relationships, 21, 305-320.
Chung, D. (2003). I am not a lonely person any more: Interpersonal relationships in computer-mediated communication. Paper presented at the annual meeting of International Communication Association, San Diego, CA.
Collins, N. L., & Miller, L. C. (1994). Self-disclosure and liking: A meta-analytic review. Psychological Bulletin, 116, 457-475.
comScore. (2008). “Top friends” ranks as most engaged Facebook application among U.S. Internet users in November 2007. Retrieved December 10, 2008 from http://www.comscore.com/press/release.asp?press=2021
Cote, J. E. (2006). Emerging adulthood as an institutionalized moratorium: Risks and benefits to identity formation. In J. J. Arnett & J. L. Tanner (Eds.), Emerging adults in America: Coming of age in the 21st century (pp. 85−116). Washington, DC: American Psychological Association.
Craig, E., Igiel, M., Wright, K., Cunningham, C., & Ploeger, N. (2007). “Will you be my friend”: Computer-mediated relational development on Facebook.com. International Communication Association (ICA) Annual Meeting.
Cummings, J., Butler, B., & Kraut, R. (2002). The quality of online social relationships. Communications of the ACM, 45, 103–8.
Dainton, M., & Aylor, B. (2001). A relational uncertainty analysis of jealousy, trust, and maintenance in long-distance versus geographically close relationships. Communication Quarterly, 49, 172-188.
Derlega, V.L., Metts, S., Petronio, S., Margulis, S. T. (1993). Self disclosure. London: Sage.
Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12, 1143-1168.
Feng, J., Lazar, J., & Preece, J. (2004). Empathic and predictable communication influences online interpersonal trust. Behavior and Information Technology, 23, 97-106.
Garson, G. D. (2009). Structural equation modeling. Retrieved on October 21, 2009 from http://faculty.chass.ncsu.edu/garson/PA765/...
Gennaro, C. D., & Dutton, W. H. (2007). Reconfiguring friendships: Social relationships and the Internet. Information, Communication & Society, 10, 591-618.
Hair, J., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Pearson Education, Inc.
Haythornthwaite, C. (2002). Strong, weak, and latent ties and the impact of new media. The Information Society, 18, 385-401.
Joinson, A. N. (2001). Self-disclosure in computer-mediated communication: The role of self awareness and visual anonymity. European Journal of Social Psychology, 31, 177-192. Kazeniac, A. (2009). Social networks: Facebook takes over top spot, Twitter climbs. Retrieved February 17, 2009 from http://faculty.chass.ncsu.edu/garson/PA765/structur.htm...
Kim, N., Lee, J. E., & Park, J. Y. (2006). “Hi! My name is Clora”: The effects of self-disclosing agents on the attitude and behavior of users. International Communication Association, 2006 Annual Meeting, 1-38.
Kline, R. B. (1998). Principles and practice of structural equation modeling (2nd ed.). New York: The Guilford Press.
Kraut, R., Kiesler, S., Boneva, B., Cummings, J., Helgeson, V., & Crawford, A. (2002). Internet paradox revisited. Journal of Social Issues, 58, 49–74.
Krikorian, D. H., Lee, J., Chock, T. M., & Harms, C. (2000). Isn’t that spatial; Distance and communication in a 2-D virtual environment. Journal of Computer-Mediated Communication, 5(4). Retrived June 20, 2009 from http://jcmc.indiana.edu/vol5/...
Levine, D. (2000). Virtual attraction: what rocks your boat. Cyber Psychology & Behavior, 3, 565-573.
MacIntyre, P. D., Babin, P. A., & Clement, R. (1999). Willingness to communicate: Antecedents & consequences. Communication Quarterly, 47, 215-229.
McAllister, H. A., & Bregman, N. J. (1983). Self-disclosure and liking: An integration theory approach. Journal of Personality, 51, 202-212.
McCroskey, J. C., & McCain, T. A. (1974). The measurement of interpersonal attraction. Speech Monographs, 41, 261-266.
McKenna, K. Y. A., & Bargh, J. A. (2000). Plan 9 from cyberspace: The implications of the internet for personality and social psychology. Personality and Social Psychology Review, 4, 57-75.
McKenna, K. Y. A., Green, A. S. & Gleason, M. E. J. (2002). Relationship formation on the Internet: What’s the big attraction? Journal of Social Issues, 58, 9–31.
Mack, D., Behler, A., Roberts, B., & Rimland, E. (2007). Reaching students with Facebook: Data and best practices. Electronic Journal of Academic and Special Librarianship, 8(2). Retrieved September 19, 2009 from http://southernlibrarianship.icaap.org/content/v08n02/mack_d01.html
Netemeyer, R. G., Bearden, W. O., & Sharma, S. (2003). Scaling procedures: Issues and applications. Thousand Oaks, CA: Sage.
Park, N., Jin, B., & Jin, S. (2009). Motivations, impression management, and self-disclosure in social network sites. Presented at the annual meeting of the International Communication Association, Chicago, IL.
Parks, M. R., & Adelman, M. B. (1983). Communication networks and the development of romantic relationships: An expansion of uncertainty reduction theory. Human Communication Research, 10, 55-79.
Parks, M. R., & Floyd, K. (1996). Making friends in cyberspace. Journal of Communication, 46, 1-17.
Pennebaker, J. W. (1989). Confession, inhibition, and disease. In L. Berkowitz (Ed.), Advances in experimental social psychology (pp. 211-244). New York: Academic Press.
Peter, J., Valkenburg, P. M., & Schouten, A. P. (2005). Developing a model of adolescent friendship formation on the internet. CyberPsychology & Behavior, 8, 423-430.
Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5) 1–6.
Ramirez, A., Jr., Walther, J. B., Burgoon, J. K., & Sunnafrank, M. (2002). Information seeking strategies, uncertainty, and computer-mediated communication: Toward a conceptual model. Human Communication Research, 28, 213-228.
Rempel, J. K., Holmes, J. G., & Zanna, M. P. (1985). Trust in close relationships. Journal of Personality and Social Psychology, 49, 95-112.
Sheldon, P. (2008). The relationship between unwillingness to communicate and students’ Facebook use. Journal of Media Psychology, 20(2), 67-75.
Sheldon, P., & Honeycutt, J. (2008). A structural equation model of oral communication and Facebook use. Paper presented at the annual meeting of the National Communication Association, San Diego: CA.
Steinfield, C., Ellison, N., & Lampe, C. (2008). Social Capital, Self-esteem, and Use of Online Social Network Sites: A longitudinal analysis. Journal of Applied Developmental Psychology, 29, 434−445
Steinfield, C. B., & Fulk, J. (1990). The theory imperative. In J. Fulk & C. B. Steinfield (Eds.), Organizations and communication technology (pp. 13-25). Newbury Park, CA: Sage.
Subrahmanyam, K., Reich, S. M., Waechter, N., & Espinoza, G. (2008). Online and offline social networks: Use of social networking sites by emerging adults. Journal of Applied Developmental Psychology, 29, 420-433.
Tabachnick, B. G., & Fidell, L. S. (1996). Using multivariate statistics (3rd ed.). New York: Harper Collins.
Tapscott, D. (1998). Growing up digital: the rise of the Net generation. New York: McGraw- Hill.
Tidwell, L. C., & Walther, J. B. (2002). Computer-mediated effects on disclosure, impressions, and interpersonal evaluations: Getting to know one another a bit at a time. Human Communication Research, 28, 317-348.
Walther, J.B. (1992). Interpersonal effects in computer-mediated interaction: a relational perspective. Communication Research, 19, 52–90.
Walther, J. B. (1995). Relational aspects of computer-mediated communication: experimental observations over time. Organizational Science, 6, 186–203.
Walther, J. B. (1996). Computer-mediated communication: Impersonal, interpersonal, and hyperpersonal interaction. Communication Research 23, 3–43.
Walther, J. B. (2008). The social information processing theory of computer-mediated communication. In L. Baxter & D. O. Braithwaite, (Eds.), Engaging theories in interpersonal communication. Multiple perspectives (pp. 391-404). London: Sage.
Walther, J. B., Anderson, J. F., & Park, D. W. (1994). Interpersonal effects on computer-mediated interaction: A meta-analysis of social and antisocial communication. Communication Research, 21(4), 3-43.
Walther, J. B., & Burgoon, J. K. (1992). Relational communication in computer-mediated interaction. Human Communication Research 19, 50–88.
Wellman, B. (1997). An electronic group is virtually a social network. In S. Kiesler (Ed.), Culture of the Internet (pp. 179-205). Halesdale, NJ: Lawrence Elbraum.
Wellman, B. & Gulia, M. (1999). Net surfers don’t ride alone: virtual communities as communities. In M. Smith & P. Kollock (Eds.), Communities in Cyberspace (pp. 167– 194). New York: Routledge.
Wheeless, L. R., Frymier, A. B., & Thompson, C. A. (1992). A comparison of verbal output and receptivity in relation to attraction and communication satisfaction in interpersonal relationships. Communication Quarterly, 40, 102-115.
Wheeless, L. R., & Grotz, J. (1977). The measurement of trust and its relationship to self-disclosure. Human Communication Research, 3, 250-257.
Yum, Y., & Hara, K. (2005). Computer-mediated relationship development: A cross-cultural comparison. Journal of Computer-Mediated Communication, 11(1). Retrieved October 22, 2006 from http://jcmc.indiana.edu/vol11/issue1/...
Louisiana State University
Department of Communication Studies
136 Coates Hall
Baton Rouge, LA 70803