A review of social networking service (SNS) research in communication journals from 2006 to 2011

Defining SNS: From website-based to integrative service

In the current literature, the acronym “SNS” is frequently used, but sometimes it is unclear what exactly this refers to. In 2007, boyd and Ellison described the features of SNS and briefly summarized the development of scholarship in previous SNS literature; they proposed a definition for this form of social media, which has been widely adopted by later research. SNS was first defined as “social network site,” referring to a “web-based service that allow[s] users to 1) construct a public or semipublic profile within a bounded system, 2) articulate a list of other users with whom they share a connection, and 3) view and traverse their list of connections and those made by others within the system” (p. 211). This widely adopted definition emphasizes a distinguishing characteristic of SNSs from previous forms of social media—“the public display of connections.” Indeed, such a “crucial component of SNSs” (p. 213) is a kind of visualization of the network. Before the launch of SNS, one could not directly access network information (e.g. number of friends, mutual friends, joined groups, etc.) about others with whom one is communicating, most of which was usually intangible in previous methods of interpersonal interaction. With the help of SNS, information provided by the creators (users) and their inter-correlating connections became visible because of the computational programs embedded in the systems (Lampe et al., 2006; Tong et al., 2008). Through these self-generated and system-generated information systems, users can now easily traverse the network by clicking through one another’s friend lists on the SNS profiles. Researchers are able to generate information for analysis of the interconnectivity and structural patterns of the networks. As indicated, such functions make SNS novel, in comparison to face-to-face (FtF) interaction and previous computer-mediated communication (CMC). The communication within/among different social groups or networks has been enhanced because people can actively seek out or pull in information about others with whom they have connected on the virtual platform (Ellison et al., 2007), which allows a larger amount of social information access. Moreover, the uniqueness and integration of personal information on the profiles of SNS users (e.g. name, photo, affiliation, relationship status) decreases the uncertainty of anonymity found in some modes of CMC and provides a more consistent and transparent social interaction process across on- and offline settings. The existing literature has widely discussed the above functional innovations which confirms the validity and applicability of the definition.

In a broader sense, “SNS” can be defined as “social networking service.” This encompasses the underlying structure of the term, covering more technological features and purposes of use in daily life, reflecting the mobile, collective, and dynamic practice of social interaction, because SNS is not simply a static object but a fast-changing phenomenon, both in terms of technological features and usage patterns. It is notable that functional features have been continuously invented all through these years; for example, the evolution from Facebook’s wall to timeline. Hence, it is necessary to catch up with current developments, to link them to what we have done so far and to improve our epistemological approach in future SNS research. Future developments in both the theoretical concept and applied models are suggested to take the new changes into account via investigation. Perusal of the literature revealed various names for “SNS”; some argue that the term should be regarded as a “service” rather than a “site,” two terms that are frequently used interchangeably. The conceptualization by boyd and Ellison (2007) mainly focused on the characteristics of website-based use of SNS, for example logging into Facebook, MySpace, or LinkedIn with a browser on a personal computer (PC). Such qualifications stem from the years when SNS supported only limited mobile interactions and launched single (or few) language interfaces. Today, with the rapid development of smartphones and high-speed data transmission technologies, major SNS services are all mobile device-capable and provide multi-language interface settings.

Additionally, because of integration with positioning technology (i.e. GPS), a user can easily present his or her social activities to others in other parts of the globe. Today, most SNS, especially those with large numbers of subscribers, have become ubiquitously accessible, with fewer temporal, locational, and cultural (linguistic) constraints. The communicative activities on SNS are more synchronous with and parallel to real social life due to instant updates, other-generated information, and location specifications. This will lead to some interesting implications for future research – for instance, a life history-recording feature (both for users who are alive and those who have passed away).

Research patterns found

As indicated in a previous review study of Facebook research (Wilson et al., 2012), the perspectives, research questions, and methods are so diverse and fragmented in current SNS literature that it becomes quite difficult to produce a neat and coherent summary of all findings, even just for the studies with empirical data. Despite such difficulties, the present study attempts to outline the patterns in SNS research for further discussion. We provide descriptive analyses for the manifest content, such as objects of study and methodological preferences; for the latent content, such as thematic patterns and related findings of the identified studies, a qualitative summary was conducted. Table 2 summarizes the descriptive analyses of study objects and methodological preferences.

OPEN IN VIEWER

Table 2.

Summary of research objects and methodological preferences.

Items	Frequency (Percentage)
Specific SNS examined	Facebook – 37 (44.3%); MySpace – 11 (13.1%); Others – 8 (9.6%); Multiple platforms – 10 (11.9%); Did not indicate – 18 (21.4%).
User population investigated	University student – 46 (54.8%); General SNS/Internet user – 13 (15.5%); High school student or adolescent – 7 (8.4%); Specific group – 6 (7.1%); Young adult (age under 30) – 3 (3.6%); General population – 3 (3.6%); Did not indicate – 6 (7.2%).
Region of sample	US – 45 (53.6%); Netherlands – 8 (9.5%); Australia – 5 (6%); Multinational – 4 (4.87%); UK – 3 (3.6%); Canada – 3 (3.6%); South Korea – 3 (3.6%); Taiwan – 2 (2.4%); Hong Kong – 1 (1.2%); Germany – 1 (1.2%); Italy – 1 (1.2%); Spain – 1 (1.2%); Japan – 1 (1.2%); Did not indicate – 6 (7.2%).
Analytic approach	Quantitative – 63 (75.0%); Qualitative – 10 (11.9%); Combine – 6 (7.1%); Critical – 1 (1.2%); Conceptual/Review – 4 (4.8%).
Main method applied	Survey – 46 (54.8%); Experiment – 14 (16.7%); Content analysis – 9 (10.7%); Interview – 4 (4.8%); Ethnography/participation observation – 4 (4.8%); Textual/thematic Analysis – 2 (2.4%); Not applicable cases – 5 (5.9%).
Observation	Cross-sectional – 55 (65.5%); Longitudinal – 6 (7.1%); Not applicable cases – 23 (27.4%, 14 articles were of experimental design, 4 articles applied ethnographic methods, and 5 were conceptual/critical discussion).

Objects of study

When talking about the objects of SNS study, both the specific platforms and their users should be of concern. First, for investigation of the prevalence of SNS, the study found that, given its global popularity and large user population worldwide, Facebook was the platform (some studies call it “domain”) most investigated by scholars (44.3% of the studies). Studies on MySpace (13.1%) followed in second place, and others (e.g. Hyves, Cyworld, and LinkedIn) constituted the remaining 9.6%. A total of 10 (11.9%) studies discussed more than one SNS platform and 18 (21.4%) did not identify the specific platform for investigation, but discussed SNS in a general sense.

University students were the major user population investigated in previous SNS studies. Some studies also focused on the younger population group: middle/high school students, young people under 30, and adolescents aged 10 to 19. A few studies focused on specific SNS users for their own purposes, such as users in specific relationship statuses (Darvell et al., 2011; Young et al., 2009), university alumni (Farrow and Yuan, 2011), black users (Byrne, 2007), and new users/adopters of SNS (Baker and Moore, 2008; Parks, 2011).

As with other areas of research in communication, the United States is the undisputed pioneer of SNS studies (53.6% of the publications with empirical data were based on US samples); the Netherlands and Australia were the other two major countries, with eight articles (9.5%) based on samples from the Netherlands and five studies (6.0%) from Australia. Another four studies (4.8%) examined multinational data but still focused on western countries. Only seven studies (8.3%) were conducted in Asia (South Korea, Taiwan, Hong Kong, and Japan), which implies that the study of international/intercultural SNS use remains underdeveloped.

Methodological preferences

In addition to four conceptual articles (4.8%) and one limited to critical discussion (1.2%), 79 studies (94.0%) were done with primary data. The quantitative approach was the predominant methodological preference of SNS studies for data collection. A total of 63 (75%) articles used quantitative methods and statistics for data analysis, while 10 studies (11.9%) used pure qualitative approaches and six studies (7.1%) employed both quantitative and qualitative modes for investigation.

The sample size ranged widely from nine to 127,477 (median=236.5), depending on the selected objects (e.g. individual user, SNS profile) and methodological approach (quantitative or qualitative). It should be noted that most of the samples were not collected by the traditional probability sampling method in social science research. One possible reason is the difficulty in defining the boundaries of SNS user populations. Without a clear method of defining “SNS users” online, it was hard to obtain a comprehensive sampling frame to draw a probability sample. Probability sampling usually relies on offline population, such as university students.

In terms of the times of observation, most studies that did not use experimental or ethnographic methods were cross-sectional observations. Only a few were longitudinal, applying the panel observation method.

Survey/questionnaire was the most frequently used method (54.8%), followed by experiment (16.7%), interview (4.8%), content analysis of SNS user profiles (10.7%), ethnography/participant observation (4.8%), and thematic or textual analysis (2.4%). The rest were conceptual or critical pieces (6.0%). This study found that there were certain patterns of methodological preferences in topics. For example, studies focusing on profile maintenance or impressions (perceptions) of popularity and attractiveness primarily used the experimental method.

Thematic patterns

Existing scholarship on SNS covers a wide range of topics. Indeed, based on different research focuses and perspectives, there are many ways of classifying SNS studies. In this study, we used the four broad themes outlined by boyd and Ellison (2007: 219–222) as a reference to investigate how well SNS studies published in the past half-decade fit with such thematic patterns and, more importantly, to examine if an extended scope may have emerged. We adopted boyd and Ellison’s themes because, generally speaking, these are most typical in our database. However, we acknowledge that there are other themes researched by other SNS scholars and we have included them as the “Extended Scope in SNS Research.”

To emphasize the role of networks

As pointed out earlier, visualization of the networks and social relationships is the outstanding capability that has made SNS novel since their birth. This enables the consideration of network structure during the research process. However, given certain theoretical and methodological constraints, we found that the existing SNS research still underappreciated such features and just provided non-network explanations. This may be due to the general individualism bias in the field of communication. Most studies did not collect network information from users. Such data collection treated individuals (the units of analysis) independently and neglected the empirical proof of the influence of network structure. As SNS integrates interpersonal communicative activities and social networks, future research should pay more attention to the roles and impacts of networks. Thus, we suggest that collecting network information during investigation will advance future SNS studies because it reflects how the intercorrelations of SNS users (social actors) can affect the proposed effects of SNSs.

Adoption of the main assumptions of social network analysis (SNA) might extend our view when looking at the SNS phenomenon. First, actors are interdependent units. They interact with each other within a specific network structure rather than in equal distance. Second, relational ties (linkages) between actors are channels for transfer or “flow” of resources (either material or nonmaterial). Third, network models, focusing on individuals, view the network structural environment as providing opportunities for or constraints on individual action. In addition to the “subjective type” and “content of social networks” discussed by many studies, such as trust, feelings, norms, or support—which are generalized results of social embeddedness—future studies are encouraged to look more precisely at the structure of networks and to investigate whether and how changes in network features, such as network extensity (size, range, and density), network composition (homogeneity or heterogeneity, tie-strength), and social structural positions within the network, may moderate the relational effect of SNS. The rise of the SNS provides significant research opportunities and supplies a useful source for data collection in related network research.

To improve measures of SNS use

As media usage is an essential component of communication research, an accurate and reliable measurement of SNS use is important to theory building, operationalization of research ideas, and analyses of empirical data. From our review, we found that perceived intensity is a commonly used assessment strategy of SNS use in many quantitative studies (e.g., Ellison et al., 2007; Kalpidou et al., 2011; Utz and Beukeboom, 2011). Based on the intensity of general Facebook use, Valenzuela et al. (2009) modified the measure of intensity of Facebook groups. As people nowadays are engaging with the Internet in a more socially interactive manner, SNS use can be conceptualized and operationalized in more detail. Some studies used specific assessments involving other aspects of SNS usage, such as profile maintenance and grooming (Utz and Beukeboom, 2011), active membership in groups (Farrow and Yuan, 2011), and privacy settings (Debatin et al., 2009; Lewis et al., 2008).

The intensity scale developed by Ellison et al. (2007) is undoubtedly reliable and valid to assess a user’s perception about daily habitual use of SNS and his or her connectedness to an online community. Nevertheless, it should be noted that the measure is basically a kind of subjective reflection. The measure may lead to a tendency to report the perceived general popularity of SNS while responding to question items, similar to the measure of the third-person effect. More importantly, the measure is not directly comparable across samples and contexts.

Some scholars (Burke et al., 2010) argued that asking for friend count and time on site is sufficient to measure intensity, as attitudinal self-reports do not correlate with plausible engagement metrics and, in prior studies, attitudinal self-report measures have shown problems such as central tendency and acquiescence bias (Krosnick, 1999; Schwarz et al., 1985). It is likely to become a trend in the field to seek for possible server (system-generated) data that correlate more strongly with attitude reports. Of course, server data such as time online in the previous month may not capture a user’s full experience of engagement (Burke et al., 2010), and the simple estimation of time does not distinguish between time spent on actual social activities and that spent on solitary activities. Thus, the development of a more accurate measure of SNS use is necessary (Hargittai, 2007). Researchers are encouraged to continuously look for long-term and multidimensional SNS engagement in the next waves of study.

To rethink the nature of relationship and friendship on SNSs

Relational study is one of the main focuses in the existing SNS research. However, the definition of “relationship” in many SNS studies is actually not clear. Some other disciplines (e.g. public relations, organizational studies, international relations) in which relationships also serve as a central concept share these explication problems (Broom et al., 1997). Hence, another reflection from the present review is that SNS researchers need to pay more attention to the nature of relationships or so-called “friendships” during the investigation process.

If the relationship is regarded as relatively static, there are many ways to define or categorize it. Some of these methods of explication are nominal—for example, relative social role (e.g. parent, schoolmate, and colleague) or goal for relationship (e.g. exchange or communal relationship). This way of categorizing will place the role of the relationship as an antecedent in a conceptual model. Because the nominal approach is usually criticized as incomprehensive and incomparable, many researchers practically adopt an “alternative path” to look at relationships as dynamic process by looking at interactions and the resources (e.g. time and emotion) one commits to a relationship. However, such practice creates another problem in operationalization, particularly in quantitative research design: assessments of relational interaction can be easily mixed up with SNS (media) uses in measures. Moreover, since the self-administrative survey/questionnaire is usually preferred by SNS researchers, in most cross-sectional designs it will lead to certain difficulties in interpretation of data.

For investigation of how SNS are able to enhance or weaken social connectivity, we argue that consideration of the nature of certain relationships should be helpful and necessary. It is noted that previous studies have not paid enough attention to the nature of relationships during investigation. Instead, most generally adopt overall measures, such as overall closeness to “friends,” personal well-being, social support, or even social capital to reflect the abstract terms of online “social relationships.” This method of conceptualization and operationalization leads to uncertainty regarding the basic concept and difficulties in direct comparison of results.

Moreover, the characters of online networks, which are formed by relationships, can be private or public, open or closed, small or large, free or restrictive, commercial or noncommercial, depending on certain circumstances, interests, priorities, geographical location, technological factors, etc. This neglect of the nature of relationships and networks may lead to the dilemma of existing empirical findings showing different and even contradictory judgments or conclusions on the issue, which implies the necessity to re-evaluate the impact brought by SNS. Future research should enhance the measures and indicators of specific relationships when conducting studies on the relational enhancement effect of SNS.

To consider the dynamic adoption process of SNS (longitudinal effect)

The present study raises a call for longitudinal studies in the future to examine the impact of SNS, because consideration of the dynamic adoption process can provide a more comprehensive picture of SNA usage patterns. For example, it is widely argued that frequent communication supported by SNS activities can facilitate the formation of positive attitudes toward a relationship, while the mechanism behind it (how such positive attitudes are established and how long they will last) is usually under-discussed due to methodological limitations. Longitudinal data should be helpful to researchers for interpreting the results of psychological, relational, and social impacts, and they are needed to conclusively establish the temporal order to improve causality inference.

People usually hold the perception that SNS are strong in their abilities both to activate latent ties (e.g. friends who have lost contact for years) and to bridge new social ties (e.g. friends of friends). They believe that such strengths of SNS can compensate for disconnected or less frequently connected relationships as a result of the constraints of time and space, especially the latter. Some studies support the notion that the establishment of new ties and social bridging is a significant motivation or gratification for SNS use. However, some have also suggested that the main purpose of network extension is less important. boyd and Ellison (2007) argue that “networking” or looking to meet new people is not the primary practice for most SNS users. They believe that the most frequent interactions on Facebook are between people and their inner social circles or those with existing connections. In other words, compared to network bonding, the significance of the social bridging function is weaker among users in a longitudinal process. This may be partly due to the cross-sectional design. This is one of the discussible issues awaiting further examination via longitudinal study to look into the dynamic process of adoption practices.

Moreover, in contrast to studies in the early developmental stage of SNS research, an increasing amount of research shows less positive results, which challenge the expected effects of SNS. Vergeer and Pelzer (2009: 203) give a possible explanation for this: “(A)fter registering probably out of curiosity and peer pressure, the membership of one or multiple SNSs may just weakly associate with the actual online communication within the online network.” People can hardly enclose their entire social network in one single online social network because it is still impossible to connect or transfer several layers of social networks to a single online network. Given the limited time available for socializing, the need to maintain relationships with frequent contact places a limit on the scope of networks that can be maintained at particular levels of emotional intensity. Whether the networks differ in richness of communication cues or in network composition is unclear, but it is possible that the integration of online and offline networks will gradually change along with the adoption of SNS. Hence, rather than applying cross-sectional investigations and seldom distinguishing between the specific adoption stages of respondents, this study encourages the use of the longitudinal method for future study. Researchers can investigate the development of online communities over time and focus on factors that raise and maintain the sustainability of online communities.

To expand to cross-contextual and cross-cultural contexts

Students at both the university and the high school level were the major sampling targets for investigation. Although it is agreed that “[university] students are often forerunners in the adoption of new communication technologies and their communication networks tend to be dense and multilayered” (Lewis et al., 2008), the exclusive use of this target sample still leaves questions about the applicability of results from campus to other contexts, such as users in working environments and the elderly population. One explanation for the emphasis on student samples may be operational convenience, especially for surveys. Factors such as time available to spend on social interaction, priority placed on socializing, emotional maturity, ICT abilities, and so forth can differ from context to context. Different sample-selection criteria across studies may bring varying conclusions regarding the impacts of SNS. Thus, as mostly recommended by other fields in social science, future research should recognize the value and importance of cross-contextual and cross-cultural sampling methods.

Current research on SNS has primarily been developed in North American or European cultural contexts, and this might be problematic in that it inadequately explains the communication behavior of non-western populations. To date, little research published in the major communication journals has yet touched on the mechanism of SNS use within non-western contexts and its cultural implications for relationships and networks. Among the sampled articles, only a few pieces of work collected samples from non-western countries or discussed SNS usage among the non-white population. Future research is needed into wider cultural backgrounds, such as the Asian culture, which is deeply rooted in Confucianism, emphasizing long-term relationships, the personal influence model, humanism, face, loyalty, order, and harmony. It is likely that the usage patterns and implications of SNS in this context would be different from existing findings. Thus, future research with sound and more diverse sampling techniques will enrich the general body of knowledge.