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Why Do People Use Social Media? Why Do People Use Social Media? Empirical Findings and a New Theoretical Framework for Social Media Goal Pursuit Donna L. Hoffman Albert O. Steffey Professor of Marketing UC Riverside Donna.Hoffman@ucr.edu Thomas P. Novak Albert O. Steffey Professor of Marketing UC Riverside Tom.Novak@ucr.edu This research was supported by the National Science Foundation (Grant # IIS-1114828). Electronic copy available at: http://ssrn.com/abstract=1989586 1 Why Do People Use Social Media? 2 Why Do People Use Social Media? Empirical Findings and a New Theoretical Framework for Social Media Goal Pursuit Abstract Why do people use social media? We examine how and why people use social media in the context of their basic needs for autonomy, competence and relatedness, intrinsic and external motivations, and well-being perceptions. Results show that motivations differentially drive social media goal pursuit, and users with different primary social media goals differ in perceptions of well-being. Using these results, we develop a testable theoretical framework for social media goals defined by two higher-order dimensions that contrast the primary focus of the online interaction with the primary direction of the online interaction. The framework may be useful to further understanding of the relationship between users’ social media behaviors and subjective well-being in the context of their fundamental needs and motives. Keywords: social media, online interaction, interaction focus, interaction direction, selfdetermination theory, well-being Electronic copy available at: http://ssrn.com/abstract=1989586 Why Do People Use Social Media? 3 Why Do People Use Social Media? Empirical Findings and a New Theoretical Framework for Social Media Goal Pursuit As the Internet continues its inexorable march toward ubiquity, many are wondering what consequences for our society’s well-being lie in its path. The question is becoming more important as online social networking and “social sharing” beha; viors increase and as “alwayson” Internet use becomes more personal, being accessed as much or more on mobile devices than it is on the PC (Meeker 2010). In late 2010, it was widely reported that visits to Facebook now account for 25 percent of page views and ten percent of all Internet visits in the United States (Dougherty 2010), with Facebook surpassing Google in share of visits (Dougherty 2010). Internet users in the United States now spend more than one-quarter of their online time on social media applications like blogs and social networking sites (Nielsen Blog 2010). Google’s CEO recently announced that thirty-five hours of video are uploaded to YouTube every minute (Schmidt 2010), more than double the amount just two years ago. New social search applications like Quora, which facilitates answers to questions from one’s online friends in real-time, suggests that social media are likely to change the dynamics of organic search. Zynga, the social gaming company known for games like Mafia Wars and FarmVille, has more than 320 million users with 3 million concurrent users during peak periods (Chiang 2010) and American Express points can now be redeemed for limited editions of virtual goods to be used in Zynga games (Poletti 2010). Social commerce applications like Beautylish and Lockerz, along with social coupon sites like Groupon and Living Social are becoming increasingly popular as they incorporate user-generated content and group interaction to support shopping activities. Social networking continues to evolve with “personal networks” like Path, Gravity, Aro and GroupMe, distributed social browsing applications like Meebo and social sharing Why Do People Use Social Media? 4 organized around photos with applications like Instagram, Picplz, Twitpic and Dailybooth. As social media applications continue to proliferate and the dynamics of online social interaction continue to evolve, communication researchers are seeking to develop a deeper understanding of how and why people use social media so that theoretically consistent models linking user motivations, social media goals, and perceptions of well-being can be constructed (Hoffman 2012). The need for such models is increasingly acute as user participation in new forms of social media introduces a potential for both positive and negative outcomes on well-being. Social media allow people to connect – and re-connect – sometimes over large distances, offer opportunities for self-expression that may not always be possible offline, provide opportunities for learning and information sharing that are unprecedented, and support users’ needs to control their online experiences. Zynga’s FrontierVille game has hosted 650,000 same-sex marriages in the six months since the game went live (Chiang 2010), possibly more than have occurred in the real world. On the other hand, location-based check-in services, for example, provide opportunities to intrude on user’s privacy and safety. In early 2010, the website pleaserobme.com attracted considerable media attention by showcasing check-in updates from foursquare users who had indicated they were currently at a location other than their home, with the implication that their home was currently unprotected and represented an attractive burglary target (Siegler 2010). Despite some negative concerns, people are primarily attracted to social media for the broad range of goals that can be adopted. Hoffman and Novak (2011) argue that the fundamental interactivity of social media allows for four higher-order goals: connect, create, consume and control. Thus, social media enable and facilitate interactions that connect people. These social Why Do People Use Social Media? 5 media conversations occur through web- or mobile-based applications that people use to create (i.e. post, upload, blog) and consume (i.e. read, watch, listen to) content. Finally, social media applications give individuals a greater ability to manage their reputations and control the applications (e.g. page layout, tagging, rating) and online “settings” such as profile and privacy options. These “4Cs” capabilities of social media undoubtedly explain in part why so many people spend so much of their time using social media and why social media are so popular. Not surprisingly, this popularity has stimulated a surge of research in recent years examining social media usage. Research has identified literally hundreds of motivations underlying why people use social media in a wide variety of contexts including blogs, Twitter, virtual worlds, YouTube and many others (Novak 2008). There has also been a great deal of descriptive research examining different social media behaviors. Yet despite the plethora of research on social media usage, there is little unifying theory to guide analysis. This paper represents a first step on this path toward the development of a unifying theory. We examine two research questions in two large-scale studies and then use the results of these studies to formulate a testable theoretical framework for evaluating social media goal pursuit. Our first research question examines social media goal pursuit in the context of the core social motive of the need to relate (Fiske 2004), the additional fundamental needs for autonomy and competence (Deci and Ryan 1985), individuals’ orientation toward intrinsic and external locus of causality (Deci and Ryan 2000) and two aspects of self-esteem in the context of social identity (Luhtanen and Crocker 1992). Our second research question evaluates the relationship between social media goals and perceptions of well-being (Diener, et.al 1985; Diener, et.al. 2009). The 4Cs of connecting, creating, consuming and controlling social media experiences (Hoffman and Novak 2011) serve as our initial conceptual framework for evaluating how user Why Do People Use Social Media? 6 motivations may differentially drive social media goal pursuit and how those goals and several measures of subjective well-being are associated. The paper is organized as follows. First, we briefly summarize related work and then present our motivational framework and key research questions. In the third and fourth sections we present the results from two large-scale studies. In section five, we draw on these results to develop a theoretical framework that can support future inquiry. RELEVANT LITERATURE Social Media Motivations and Goal Pursuit Social media, which by definition involve individuals relating to each other, represent new and fertile ground for exploring what drives online social behavior. Not surprisingly, considerable research has addressed the question of why people use social media in varied contexts. Literally hundreds of motivations underlying why people use social media in a wide variety of contexts including blogs, Twitter, virtual worlds, YouTube and many others have been identified (Novak 2008). In a review of more than 30 articles that examined over 100 objectives, goals or motivations for using social media, Novak (2008) uncovered no fewer than 22 distinct motivational categories of social media use (see Table 1). These include, for example, achievement (Kuznetsov 2006), information (Weiss, Lurie, Macinnis 2008), peer pressure (Jung, Youn and McClung 2007), positive experience (Hoffman and Novak 2009), self understanding (Zhao, Grasmuck and Martin 2008) and social interaction (Lenhardt and Fox 2006), among others. While it is clear that people use social media for many different reasons, the lack of a unifying framework hinders deeper understanding of the fundamental motivations driving social media use. Why Do People Use Social Media? 7 ---Insert Table 1 about here--Positive Outcomes From Social Connections Recent research has uncovered a strong positive connection between social connections and positive outcomes. For example, the more socially active seniors are, the more likely they are to enjoy improved cognitive and motor functioning, well into their old age (Yaffe, et al. 2009). Another recent study found that the more time seniors spent socializing, the less motor functions declined (Buchman, et al. 2009). Intriguingly, one study has documented a relationship between the size of a person’s social network and their perception of pain: patients with smaller networks report more pain and patients with larger networks report less pain (Mitchinson, et. al 2008). This finding is interesting because it suggests that larger social networks, regardless of the quality of connections, can have positive influences on well-being. Jetten, et al. (2009) reviewed a number of studies in this domain and concluded that individuals who are members of many diverse social networks are more resilient and experience more mental and physical well being compared to individuals who are not as socially connected. Similar positive benefits may also accrue from online social connections. As the Internet continues to diffuse widely through our society, individuals find it easier to keep in touch with their acquaintances (what Granovetter (1973) calls “weak ties”) and use the Internet to strengthen the bonds underlying their close friends (“strong ties”). Social media also offer people opportunities to express themselves and connect with others even if they are able to derive benefit from such opportunities offline. Collins and Wellman (2010) observed that the more people use the Internet, the more connected they are both online and offline. Bessière, et al. (2008) found that Internet users motivated by the need to communicate with friends and family had lower depression scores than individuals motivated to use the Internet to meet new people and chat online. Wellman, et al. (2001) found that online participation actually supplemented Why Do People Use Social Media? 8 face-to-face and telephone interactions by extending another avenue for communication, although the heaviest users did not reap the benefits to the same degree. Benefits of online communication appear to extend to new relationships as well. McKenna, Green and Gleason (2002) found that participants who met each other for the first time through online chat liked each other more based upon that interaction than did participants who met face-to-face for the first time, and related research found that individuals interacting through online chat are better able to express their true self than individuals in face-to-face interaction (Bargh, McKenna, & Fitzsimons, 2002). Thus, online networks are seen as a beneficial tool that compliments the tools users already use to maintain their interconnectedness. As social networks proliferate, communication researchers are turning their attention to the psychological benefits of online participation. For example, Facebook can help users maintain their close relationships at the same time that it helps build and maintain weak ties among large groups of distant friends and acquaintances, leading to an increased sense of selfesteem in new college students (Ellison, Steinfield, and Lampe 2007). Novak (2012) has found that virtual worlds as a social environment offer the potential as an intervention to improve wellbeing, at least in part by substituting for physical consumption and physical presence. While studies seem to suggest that Internet use is likely to be positively associated with subjective well-being, it is not clear under what conditions we might expect the same beneficial effects for social media. It does seem reasonable that online use might generally be expected to contribute to well-being because it satisfies basic needs for relatedness. Yet, because the impact of Internet use on a person’s well being is likely to be a function of the goals people have for interacting (Bargh and McKenna 2004), a full understanding of the impact of social media use on well-being will necessarily require a detailed motivational account. Why Do People Use Social Media? 9 ANTECEDENTS AND CONSEQUENCES OF SOCIAL MEDIAL GOALS Basic Need Satisfaction. We contend that social media use offers individuals the opportunity to satisfy basic psychological needs. Whether or not these needs are satisfied depends on the goals individuals pursue while engaging in social media behavior and the motivations underlying this goal pursuit. Ultimately, whether individuals experience positive outcomes related to psychological well-being and physical health depend on this motivational structure. Consistent with Fiske’s (2004) delineation of core social motives and Baumeister and Leary’s (1995) hypothesis that the need to belong is a fundamental motivation, we argue that individuals use social media because they are fundamentally motivated to connect with each other and that using social media has the potential to provide these connections. In addition to this need for relatedness, we consider that individuals seek to satisfy needs for autonomy and competence (Deci and Ryan 1985). Autonomy refers to an internal perceived locus of control (de Charms 1968) or a sense that one’s behavior is self-determined, while competence describes a sense of self-efficacy where one has the capabilities to meet the challenges presented by the task. Tamborini, et. al. (2010) have recently shown that media enjoyment results from the satisfaction of fundamental needs. Thus, need satisfaction should have important implications for how people experience social media use. Individual Motivational Orientation. According to self-determination theory, the reasons that people are motivated to engage in a particular behavior are governed by their motivational orientation (Deci and Ryan 2000). To the extent that behaviors are internalized or intrinsically motivated, individuals are expected to exhibit greater enjoyment, satisfaction and general wellbeing from those behaviors (see, for example, Ryan and Deci 2000). Intrinsic motivation for a Why Do People Use Social Media? 10 behavior is supported when the basic psychological needs of competence and autonomy experienced during that behavior are satisfied. Behaviors that are extrinsically motivated can vary in the degree of competence and autonomy they satisfy. Because a perceived internal locus of causality appears so strongly implicated in positive subjective experiences, the extent to which extrinsically motivated behaviors are internalized will also relate to positive subjective experiences like well-being. Ryan and Deci (2000) suggest that the need for relatedness, along with competence and autonomy, can aid in internalizing behaviors that are often extrinsically motivated. Although a considerable amount of research has investigated the role of autonomy and competence in motivating behavior, much less is known about the impact of relatedness needs (Pittman and Zeigler 2007). Individuals for whom social media satisfies these needs should experience a positive impact on well-being (Sheldon, Elliot, Kim, & Kasser, 2001). This line of reasoning is closely related to the idea of optimal online experience conceptualized by Hoffman and Novak (1996). Individuals who experience flow during their online navigational experiences are more likely to achieve positive outcomes compared to individuals who cannot attain these compelling online experiences (Novak, Hoffman and Yung 2000). Collective Self-Esteem. Recently, Leary (2007) has argued that self-esteem serves as a measure or sociometer of an individual’s relational value to other people. This motivational perspective suggests that self-esteem helps individuals increase their social value and is not pursued for its intrinsic value. Because social media are, by definition, social, it stands to reason that self-esteem may be an important predictor of social media goal pursuit. We argue that the relevant concept of self-esteem is a collective one that captures an individual’s evaluation of their self-esteem in the context of their social identity (Luhtanen and Crocker 1992). Two Why Do People Use Social Media? 11 components of collective self-esteem are highly likely to motivate goal pursuit: private collective self-esteem and importance to identity collective self-esteem. Private self-esteem taps an individual’s judgment of the value they place on their social groups and identity self-esteem captures the importance of these social groups to their self-concept. We theorize that these components of collective self-esteem motivate users to pursue a positive online social identity among the people in their online social groups and differentially predict social media goal pursuit. Overview of Studies 1 and 2 We designed two large-scale studies to address the primary research questions of how and why people use social media in the context of their needs, motivations, and perceptions of well-being. In study 1 we elicit consumers’ primary goals for using social media and develop a goal typology based upon these elicited goals. We expect that the 4Cs (connect, create, consume, and control) will explain a substantial proportion of the variation among consumer’s social media goals. We also determine how well the pursuit of each of the 4C’s can be predicted from and are theoretically consistent with constructs identified in our literature review - goal-level motivations, individual-level needs/motivations, and related social media characteristics. In study 2, we develop specific goal statements based upon the goals identified in study 1 and ask people to tell us which of these social media goals makes them happy. Our primary interest in study 2 is to evaluate whether individuals with different primary 4Cs social media goals differ in terms of their satisfaction with life as a whole, happiness with social media in general and the degree to which pursuing specific social media goals makes them happy. Why Do People Use Social Media? 12 STUDY ONE Participants. A random sample of 1400 English-speaking participants from a university operated online panel were emailed invitations to a web-based survey. A total of 340 participants (24% of those invited) completed all questions. Demographics of those completing the survey closely mirrored that of the sampling frame of invited panelists. Of 1400 invited panelists, 70% were female, 52% completed at least a college education, and 57% were over 40 years of age. In the final sample of 340 panelists, 72% were female, 56% completed at least a college education, and 59% were over 40 years of age. Procedure. Participants rated their involvement and knowledge with social media, and provided brief written descriptions of their top five specific goals when using social media. Participants then rated the degree to which each of their top five goals was: 1) relevant to connect, create, consume and control goals (based on descriptions derived from our theoretical constructs), 2) related to autonomy, competence and relatedness needs (derived from Sheldon, et al. 2001), and 3) related to intrinsic and external locus of causality motivations (derived from Sheldon and Elliot 2000 and Ryan and Connell 1989). We also measured two aspects of respondents’ social identity in the context of their social media use: private collective self-esteem and importance to identity collective self-esteem (scales adapted from Crocker et. al.1994). Analysis and Results: Goal Coding. A total of 1700 social media goal verbatims were obtained from the 340 participants. These were classified into a smaller set of 27 more general social media goals to more clearly understand how different types of social media goals correspond to the four broad underlying goals of connect, create, consume and control. Figure 1 plots the group centroids for these 27 goal types, based upon a canonical discriminant analysis predicting social media goals from the 4Cs ratings (connect, create, consume, control) of each of Why Do People Use Social Media? 13 the 1700 goals, with the 27 goals serving as the groups. The first two dimensions plotted in Figure 1 account for 78% of the variance among the 27 social media goals, showing that the 4Cs provide a good higher-level explanation of specific social media goals. Differences among the 27 social media goals in terms of consume, connect and create goals are well represented in the plot. Control less clearly discriminates among the 27 specific goals, suggesting that control “cuts across” goals and relates to how a given goal is approached. ---Insert Figure 1 about here--Analysis and Results: Multilevel Model Predicting Goals from Needs and Motivations. The 27 social media goal types were further classified as either social (49.8% of goals) or nonsocial (50.2% of goals). Examples of social goals were connecting with friends and family, using social media to meet new people, sharing pictures and videos with friends, and reconnecting with people one had lost touch with. Non-social goals included reading the news, learning about popular events, listening to music, downloading videos, finding deals, and researching products. The data collected in study 1 are multilevel, in that five social media goals are nested within 340 individuals. The set of five goals elicited for each person may differ considerably from person to person, with individual level heterogeneity leading to correlated errors in goallevel ratings. Thus, multilevel linear models (also known as linear mixed models, hierarchical linear models, or random effects models) were used to account for correlated errors in the multilevel data e.g. Hox 2002; Kreft and deLeeuw 1998). Level 1 variables are those measured at the goal level (1700 observations) while level 2 variables are those measured at the individual level (340 observations). Multilevel models were fit separately to each of four dependent measures (i.e. the 4Cs goal-specific ratings of connect, create, consume, and control). We first fit the null model Why Do People Use Social Media? 14 containing only a random intercept in order to estimate the intra-class correlation, ρ, and to provide baseline level 1 and level 2 residual variances for comparison with our complete model. Intra-class correlations in the null model reported in Table 2 show that the greatest heterogeneity among individuals is in adopting control goals (ρ = .62) and that the least heterogeneity is in adopting connect goals (ρ = .32), with create goals (ρ = .49) and consume goals (ρ = .42) lying in between. Thus, consumers are relatively homogeneous in their pursuit of connect goals, but differ in the extent that they pursue control goals. ---Insert Table 2 about here--The complete model fit to each of the four dependent measures includes a random intercept and the following additional fixed effects: 1) a level 1 binary variable for goal type (social vs. nonsocial); 2) within person mean centered level 1 measures of autonomy, competence, relatedness, intrinsic LOC and external LOC (i.e. means for each individual were subtracted from the goal-specific ratings); 3) between person level 2 individual means (calculated over each person’s five goals) of autonomy, competence, relatedness, intrinsic LOC and external LOC; and 4) dispositional level 2 measures of private collective self-esteem, importance to identity collective self esteem, social media knowledge, and social media involvement, all level 2 predictors measured at the individual level. Note that the use of level 1 (centered goal-specific ratings subtracting the individual means) and level 2 (the reintroduced subtracted means) versions of autonomy, competence, relatedness, intrinsic LOC and external LOC allows independent assessment of within-person and between-person effects for these five measures (e.g. Kreft and deLeeuw 1998). The complete multilevel model allows us to determine whether and how the 4Cs (i.e., connect, create, consume and control goals) can be predicted from needs, motivation, and Why Do People Use Social Media? 15 dispositions, taking into account both within person (level 1) and between person (level 2) variation in the 4Cs. From table 2, the degree of within-person variation that can be explained (i.e. R2within) ranges from .07 for consume to .37 for connect, and the degree of between-person variation that can be explained (i.e. R2between) ranges from .21 for consume to .64 for create. Having established that we can explain a substantial portion of both within and between-person variation, we turn next to understanding what predicts the 4Cs Table 3 presents fixed parameter estimates for the complete model. The results show that the pursuit of connect, create, consume, and control goals are differentially predicted by needs, motivations, and dispositions. When broadly categorized as social or non-social, connect goals are more likely to be characterized as social (B = .54, p < .01), and consume goals as non-social (B = -.33, p <.01). We note that this interpretation is consistent with projections of the 4C’s vectors on the horizontal axis in Figure 1. Need satisfaction predicts the pursuit of 4Cs goals in different ways for different goals. For connect goals, only relatedness need satisfaction is significant, both at level 1 (B = .38 , p < .01) and at level 2 (B = .36, p < .01). This indicates that the satisfaction of relatedness needs predicts whether a goal is characterized as a connect goal, both 1) within individuals (across the set of five goals an individual herself pursues), and 2) across individuals (based upon the mean of all five goals for each individual). In other words, relatedness satisfaction predicts pursuit of connect goals both in the micro context of the specific goals that a person pursues, as well as in the macro context of individual differences in how people pursue goals. ---Insert Table 3 about here--Create goals, on the other hand, are predicted at level 1 by autonomy (B = .18, p < .01) and competence (B = .25, p < .01), and also at level 2 by competence (B = .46, p < .01) and Why Do People Use Social Media? 16 relatedness (B = .12, p < .05). Similarly, control goals are predicted at level 1 by both autonomy (B = .16, p < .01) and competence (B = .18, p < .01), but diverge from create goals at level 2 by being predicted only by autonomy (B = .39, p < .01). Thus, at level 1, relative to all other goals an individual pursues, autonomy and competence predict pursuit of both create and content goals. However, when considering broader individual differences (i.e. averaged across all the goals an individual pursues), mean competence and relatedness predict the mean pursuit of create goals, and mean autonomy predicts the mean pursuit of content goals. Consume goals are least predicted by satisfaction of fundamental needs, with the exception that the level 2 coefficient for competence is significant (B = .19, p < .01), indicating individual differences in mean satisfaction of competence needs predicts an increase in mean pursuit of control goals. Together, these results strongly support the idea that the types of needs that are satisfied predicts the types of goals people pursue. Motivation for pursuing a goal is also related to type of goal pursued. Goals involving consuming content are predicted by intrinsic motivation, with significant level 1 (B = .19, p < .01) and level 2 (B = .32, p < .01) coefficients. Conversely, goals involving creating content are predicted by external motivation, with significant level 1 (B = .06, p < .05) and level 2 (B = .11, p < .01) coefficients. Control goals are also predicted by external motivation, although only the level 2 coefficient is significant (B = .26). The motivation of connect goals appears to be more complex. Within the set of goals a given individual pursues, external motivation predicts connect goals (level 1 B = .11, p < .01). However, considering the average of all goals that are pursued by a person, individual differences in mean intrinsic motivation predicts the mean pursuit of connect goals (level 2 B = .19, p < .01). Why Do People Use Social Media? 17 Last, there are some relationships of individual dispositions with goal pursuit. As these are all level 2 relationships, these predict the average of an individual’s five goals. Connect goals are predicted by individuals’ private collective self-esteem (i.e. their positive evaluations of the social media groups they belong to; B = .16, p < .01). Create goals, on the other hand, are predicted by their importance to identity (B = .11, p < 05) and by involvement with social media (B = .17, p < .01). Control goals, likely due the prerequisite level of technical expertise with social media applications, are predicted by one’s knowledge about social media (B = .20, p < .01). Together, these results show sharp distinctions in the prediction of connect goals, which largely involve other people, and create goals, which largely involve content. Control goals some similarities in motivation to create goals, and consume goals appear to be related in a fairly straightforward manner to intrinsic motivation. Having established the relationship of goal pursuit to needs satisfaction, motivation, and individual dispositions, we now consider the implications of social media goal pursuit for well-being in study 2. STUDY TWO Participants. A random sample of 396 English-speaking participants from a university operated online panel were emailed invitations to study 2 and a total of 208 participants (53% of those invited) completed all questions. Demographic composition was similar to study 1: 73% were female, 58% completed at least a college education and 58% were over 40 years of age. Procedure. Based upon the goal verbatims obtained in study 1, we created 27 statements describing a broad range of specific goals people have for using social media, for example “reconnect with people I’ve lost touch with,” “network for business or professional purposes,” or “find information about my interests.” Participants rated each of the 27 goal statements on a 5- Why Do People Use Social Media? 18 point scale according to the degree pursuing each of the 27 goals makes them happy (1=makes me very slightly or not at all happy, 5=makes me extremely happy). Participants then indicated which one of the 4Cs primary social media goals (connect, create, consume, or control) best described their use of social media, rated the overall extent to which using social media makes them happy (1=very slightly or not at all”; 5=”extremely”, and completed the Satisfaction with Life Scale (Diener et al.1985) and the Flourishing Scale (Diener et al. 2009). Analysis and Results: Goal Structure. Principal axis factor analysis with direct oblimin rotation (delta=0) was used to extract seven correlated factors explaining 67% of variance from the 27 goal statements rated on the degree to which they make one happy. Correlations among the seven factors ranged from .02 to .40, with median factor correlation of .24. Table 4 summarizes our interpretation of the factors, based upon the structure matrix of correlations above .5. To clarify the structure of the seven correlated factors, a higher-order factor analysis using varimax rotation was performed to extract two uncorrelated factors that explained 59% of the variation in the seven correlated factors. Figure 2 shows that the seven correlated factors lie in a two-dimensional space defined by whether social media goals involving content (higherorder factor 1) or people (higher-order factor 2) make one happy. Thus, there are two broad domains of well-being (Hagerty et al., 2011) which may be considered when evaluating one’s quality of social media life (Novak 2012). ---Insert Table 4 about here-----Insert Figure 2 about here--Analysis and Results: Predicting Well-Being from Goals. Four mutually exclusive groups were defined from the primary 4Cs goal that participants said best described their social media use, with the resulting distribution: connect (26%), create (16%), consume (45%) and control Why Do People Use Social Media? 19 (13%). A series of univariate single-factor ANOVAS tested between-group differences in primary goal for five measures of subjective well-being: satisfaction with life scale, flourishing scale, social media happiness, and factor scores on the two higher-order factors (i.e., degree to which content-interaction and person-interaction make one happy). Table 5 reports means and significance tests. Satisfaction with life (p=.179 n.s. for omnibus F test) and flourishing (p=.020) are highest for individuals whose primarily social media goal is to create, while those whose primary social media goal is to connect are happiest with their overall social media use (p=.006). In general, we note that connect and create goal orientations both produce higher life and social media well-being than either consume or control motivations. However, when we consider the specific type of social media use, the last two rows of Table 5 shows that individuals whose primary social media goal is to create are the happiest when pursing goals involving contentinteraction, while those whose primary social goal is to connect are happiest when pursuing goals involving person-interaction. ---Insert Table 5 about here--To probe these last two results in more detail, we calculated mean happiness on each of the seven factors for each primary 4Cs goal group. The factor means are presented in Figure 3, organized from left-to-right following the structure uncovered in Figure 2. The lines in Figure 3 represent the primary 4Cs social media goals. Clear differences can be observed between users whose primary goal is to connect and those whose primary goal is to create, with “connectors” happiest when pursing goals involving person-interaction (socialize, update status) and “creators” happiest when pursing goals involving content-interaction (shop, learn, network). Individuals whose primary goal is either to control or consume are generally the least happy across all 7 goal factors; however, those with control goals are happiest when socializing, having Why Do People Use Social Media? 20 fun with media, while those with consume goals are relatively happiest while learning and shopping. ---Insert Figure 3 about here--Toward a New Theoretical Framework for Organizing Social Media Goals Results from the two studies led us to re-evaluate the initial 4Cs framework underlying our analyses. The empirical results suggest that there may be value in organizing the four Cs social media goals into a richer theoretical framework in which the range of social media goal behaviors available to users is uniquely determined by two broad interactivity dimensions that specify the 1) focus of the interaction, and the 2) direction of the interaction. These dimensions of interactivity differ from those proposed by other researchers which focus on perceived interactivity (e.g. Sohn and Lee 2005; Wu 2000) or on the functional aspects of a medium (e.g. Coyle and Thorson 2001; Laurel 1990; Steuer 1994). Our dimensions, in contrast, are defined by the objectives people have when using the medium of social media. Our dimensions are functional to the extent they specify how structural aspects of social media enable different types of user goals, and are perceptual to the extent they correspond to the way people choose to interpret social media in the pursuit of their own goals. The interaction focus dimension refers to whether individuals have as their primary objective to connect with other people (in which case the social media applications themselves recede in importance) or control their usage through applications (in which case the people recede in importance). The interaction direction dimension refers to whether individuals are focusing primarily on consuming social media content or primarily creating it. These terms are used in a broad context with consume referring to content that “comes to” the user (i.e. also find, get, acquire, consume, download or receive content), and create referring to content that “comes Why Do People Use Social Media? 21 from” the user (i.e. also meaning give, send, create, upload, present or distribute content). Note that this is not equivalent to an active vs. passive distinction because online, all interactions have at least some degree of activity (Hoffman and Novak 1996). In our theoretical framework, the 4Cs goals corresponding to particular values on each interaction dimension give rise to symmetric social media goal pairs, e.g. “connect-consume” (viewed as theoretically equivalent to “consume-connect”). The framework is shown in Table 6. Each quadrant of the theoretical framework is illustrated using exemplar verbatims drawn from study 1. For example, individuals may have the “connect-consume” goal of observing their child’s social networking behavior on Facebook, the “connect-create” goal of sharing YouTube videos with friends, the “control-consume” goal of browsing news and current events on popular online media sites like Huffington Post or the “control-create” goal of managing their Twitter privacy settings. ---Insert Table 6 about here--In the “connect-consume” goal pair, the primary focus of the interaction is on connecting with other people and the primary direction of the interaction is on consuming content. Goals in this connect-consume quadrant involve individuals consuming user-generated content created by others (Me Other People). Similarly, for the “connect-create” goal pair, the primary focus of the interaction is on connecting with other people, but now the primary direction of the interaction is on creating user-generated content for others to consume (Me Other People). The other two quadrants are similarly defined. The quadrant labeled “control-consume” identifies social media goals in which the primary focus of the interaction is on controlling the applications or social media environment itself in which those applications reside and the primary direction of the interaction is on consuming content. Goals in this quadrant involve Why Do People Use Social Media? 22 individuals finding user-generated content and learning new things through applications and the online environment, rather than on connecting with other people (Me Applications). The “control-create” quadrant has the same interaction focus as the “control-consume” quadrant, but identifies social media goals for which the primary direction of the interaction is on creating content through those applications or the social media environment. One obvious example is when users manage and organize their reputations and social media settings (Me Applications). These four quadrants of our 2x2 framework were obtained by crossing the endpoints of our two interactivity dimensions. But because our dimensions actually define continua of interaction, a more complete theoretical framework would actually specify five additional, intermediate quadrants that are obtained when either or both the focus of the interaction and the direction of the interaction are in the center of the respective continuum. For example, when the primary focus of the interaction involves both people and applications and the primary direction of the interaction involves both content that comes from you and comes to you, we would obtain the centermost quadrant in a more comprehensive 3x3 framework. The other intermediate quadrants are similarly defined. For the sake of parsimony we present only the four quadrants defining the outer 2x2. Although individuals pursue many different social media goals over time, a much more limited set of goals is primary in any particular situation. We propose that when an individual pursues a given social media goal, their social media behavior will be driven by a particular combination of the focus of the interaction and the direction of the interaction in which a single focus and a single direction dominate. Thus, only one goal combination is likely to be primary at any one point in time. Why Do People Use Social Media? 23 Future Directions We believe this framework may be useful to support more structured examinations of the relationship between social media goals and user response in interactive media environments. A fruitful direction for future communication research would be to test the hypothesized two dimensional structure implied by Table 6 (i.e. an interaction focus characterized by connecting with other people vs. controlling applications and an interaction direction characterized by creating vs. consuming content), and the validity of the four (or nine) social media goal types evaluated in the context of the 2x2 (or 3x3) theoretical framework. A validated framework could be used to develop scales to measure pursuit of each social media goal pair (connect-consume, connect-create, control-consume, and control-create). Such scales could then be used to further refine and empirically extend the framework to include important communication constructs likely to impact social media goal pursuit such as need satisfaction. Additional research directions include relating social media usage in the context of the interaction dimensions to key outcomes like individual well-being and to increasing our understanding of how social media communication is impacted by individual differences. Concluding Remark Using a simple 4Cs framework, we found in two large-scale studies empirical evidence that fundamental needs and motivations differentially drive social media goal pursuit and that users with different primary social media goals differ in their perceptions of well-being. 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Why Do People Use Social Media? 28 Table 1: Twenty-Two Distinct Motivational Categories of Social Media Use Achievement (Barnes 2007, Cook 2008, Jung, Youn and McClung 2007, Kuznetsov 2006, Li and Bernoff 2008, Stoeckl, Rohrmeir and Hess 2007, Trammell et al.2006,Yee 2006, Yee 2007) Peer pressure (Jung, Youn and McClung 2007, Li and Bernoff 2008) Affinity (Li and Bernoff 2008, Ridings and Gefen 2004) Routinized (Trammell et al.2006, Jung, Youn and McClung 2007, Stoeckl, Rohrmeir and Hess 2007) Altruism (Butler et al.2002, Cook 2008, Kuznetsov 2006, Li and Bernoff 2008, Nov 2007) Self augmentation (Schotz 2008) Ambient intimacy (Reichelt 2007, Schotz 2008) Self expression (Barnes 2007, Daugherty, Eastin, Bright 2008, Java et al.2007, Jung, Youn and McClung 2007, Lenhardt and Fox 2006, Li and Bernoff 2008, Nuxoll 2006, Trammell et al.2006, Zhao, Grasmuck and Martin 2008) Autonomy (Kuznetsov 2006) Collaborate (Kuznetsov 2006, Nuxoll 2006) Curiosity (Kapoor, Konstan and Terveen 2005, Li and Bernoff 2008, Schotz 2008) Emotional (Ridings and Gefen 2004, Schotz (2008) Entertainment (Barnes 2007, Cho 2007, Jung, Youn and McClung 2007, Nov 2007, Ridings and Gefen 2004, Schotz 2008, Stoeckl, Rohrmeir and Hess 2007, Trammell et al.2006) Influence (Butler et al.2002, Lenhardt and Fox 2006, Nov 2007, Schotz 2008, Sun, Rubin, and Haridakis 2008) Information (Barnes 2007, Cho 2007, Java et al.2007, Lenhardt and Fox 2006, Ridings and Gefen 2004, Sun, Rubin, and Haridakis 2008, Trammell et al.2006, Weiss, Lurie, Macinnis 2008) Instrumental (Barnes 2007, Cook 2008, Daugherty, Eastin, Bright 2008, Schotz 2008, Sun, Rubin, and Haridakis 2008, Weiss, Lurie, Macinnis 2008) Positive Experience (Barnes 2007, Hoffman and Novak 1996, Hoffman and Novak 2008, Yee 2006, Yee 2007) Self esteem (Daugherty, Eastin, Bright 2008, Nov 2007) Self understanding/knowledge (Barnes 2007, Daugherty, Eastin, Bright 2008, Jung, Youn and McClung 2007, Lenhardt and Fox 2006, Li and Bernoff 2008, Nuxoll 2006, Trammell et al.2006, Zhao, Grasmuck and Martin 2008) Share (Java et al.2007, Stoeckl, Rohrmeir and Hess 2007, Lenhardt and Fox 2006) Social capital (Ellison, Steinfield and Lampe 2007, Li and Bernoff 2008, Ridings and Gefen 2004) Social interaction (Barnes 2007, Butler et al.2002, Cho 2007, Daugherty, Eastin, Bright 2008, Java et al.2007, Jung, Youn and McClung 2007, Lenhardt and Fox 2006, Miura and Yamashita 2007, Nuxoll 2006, Sun, Rubin, and Haridakis 2008, Trammell et al.2006, Weiss, Lurie, Macinnis 2008, Yee 2006, Yee 2007) Why Do People Use Social Media? Table 2. Variance Estimates for Null and Final Linear Mixed Models Dependent Variable: Connect Create Consume Control Null Model Level 1 variance (residual) Level 2 variance (intercept) intra-class correlation (ρ) AIC 1.02* .47* .32 5267.34 .98* .93* .49 5396.58 .86* .62* .42 5103.81 .74* 1.22* .62 5071.25 Complete Model Level 1 variance (residual) Level 2 variance (intercept) R2 within (vs. Null Model) R2 between (vs. Null Model) AIC .64* .18* .37 .62 4427.05 .85* .34* .14 .64 4973.78 .81* .49* .07 .21 4994.54 .66* .63* .11 .48 4774.18 *p < .05 Table 3. Fixed Parameter Estimates for Complete Model Dependent Variable: Connect Create Intercept .87** -.31 Consume Control 2.20** -.33 .01 .18** .25** .06* .03 .06* -.33** -.07* -.07* -.05 .19** -.02 -.03 .16** .18** .00 .04 .04 .00 .46** .12* .03 .11** -.06 .11* .17** .07 -.10 .19** -.04 .32** .08 .00 -.09 .04 .03 .39** .11 .00 -.11 .26** -.02 .10 .06 .20** Level 1 social vs. non-social goal autonomy (centered) competence (centered) relatedness (centered) intrinsic LOC (centered) external LOC (centered) .54** .00 .06 .38** -.02 .11** Level 2 autonomy (mean) competence (mean) relatedness (mean) intrinsic LOC (mean) external LOC (mean) private self-esteem importance to identity social media involvement social media knowledge .04 -.02 .36** .19** .05 .16** -.08* .05 -.01 **p<.01, *p<.05 29 Why Do People Use Social Media? Table 4. 7 Social Media Goal Factors Factor 1 Learn Factor 2 Socialize Factor 3 Network Factor 4 Update Status Factor 5 Shop Factor 6 New People Factor 7 Media Fun learn about new things (.74), find information about interests (.67), interact with groups that share my interests (.62), find news/events (.59), share information/news (.58), explore (.78), find opinions (.57), help others (.54) socialize with people I know (.87), socialize with friends (.85), socialize with family (.75), reconnect with people I’ve lost touch with (.56), share photos, music, videos (.51) network for business/professional purposes (.88), promote myself or my business (.87) tell people what I’m doing (.79), find out what others are doing (.73), pass the time (.52) find information about products (.79), find good deals (.73), explore (.54), find information about interests (.53), learn about new things (.52) meet new people (.81), socialize with anonymous people (.76) find music/videos (.64), have fun (.58), share photos, music, videos (.54), pass the time (.52) Table 5: Primary 4Cs Goal Mean for 5 Well Being Indicators Primary 4Cs Goal mean Satisfaction with Life Scale (Diener et al.1985) Flourishing Scale (Diener et al.2009) Social media use, overall, makes you happy Content-interaction makes you happy Person-interaction makes you happy ANOVA Connect Create Consume Control p-value n=53 n=34 n=94 n=27 .179 4.88 4.59 4.51 5.14 .020 .006 5.85 3.49 6.15 3.32 5.59 2.96 5.81 3.19 .001 .001 -0.16 0.43 0.63 0.11 -0.07 -0.26 -0.24 -0.09 30 Why Do People Use Social Media? Table 6: New Theoretical Framework for Social Media Goals CONNECT WITH PEOPLE CONTROL APPLICATIONS Focus of the Interaction (continuum from people to applications) Direction of the Interaction (continuum from consume to create) CONSUME CONTENT CREATE CONTENT Connect-Consume Connect-Create Find out what other people are doing Locate friends I’ve lost touch with Observe my child’s Facebook behavior Tell people what I am doing Post videos for family to see Discuss topics with other dentists Me Other People Me Other People Control-Consume Control-Create Learn about new things Find info about news and events Find deals/products Manage my privacy settings Tag articles on Digg Maintain my LinkedIn profile Me Applications Me Applications 31 Why Do People Use Social Media? Figure 1. Discriminant Analysis Predicting 27 Goal Types from 4C’s 32 Why Do People Use Social Media? Factor 2: person-interaction make you happy 1.000 F2 Socialize .800 F4 Update F7 Media Fun .600 F6 New People .400 F3 Network .200 .000 .000 -.200 -.200 F1 Learn F5 1.000 Shop Factor 1: content-interaction makes you happy .200 .400 .600 .800 high happiness Figure 2: Higher-Order Factor Analysis of 7 Social Media Goal Factors .600 .500 .400 CREATE CONNECT .300 .200 .100 low happiness .000 -.100 -.200 -.300 CONSUME CONTROL -.400 F2 Socialize F4 Update Status F7 Media Fun F6 New People F3 Network F1 Learn Figure 3. Mean Happiness for Seven Social Media Goal Factors (lines represent primary 4Cs goal) F5 Shop 33