2.1. Social support provision: From support receiver to support provider

Scholars have dedicated significant efforts to social support research since the 1970s. Over the course of several decades, numerous studies have been conducted to gain insights into the factors that maximize the effects of social support [10,11], the various benefits it offers [12–14], the role of social networks in receiving social support [5], and the effects of one’s network position on receiving different types of social support [4,6]. Consistently, these studies have demonstrated that social support can significantly enhance the well-being of recipients [15], its effectiveness is particularly pronounced when the recipient is under high levels of stress [10], and the type of social support received is influenced by one’s position within the network [6]. While these studies have shed light on various aspects of social support, they have predominantly focused on the perspective of recipients who seek social support. Consequently, our understanding of the other side—the providers who supply social support—remains limited.

Social support exchange is analogous to a market transaction. Just as understanding the motivations and needs of both the demand and supply sides is crucial in comprehending market transactions, our understanding of social support exchange can be significantly enhanced by gaining a balanced understanding of both social support reception and provision. Specifically, our study aims to address the following inquiries: How does the social context or network, formed through social interactions and support exchanges, contribute to the promotion of social support provision? What types of social capital emerge within networked relationships, and how do they influence the provision of social support in OSGs?

Prior studies have underscored the significance of comprehending social support provision within the context of social factors, such as social norms [16], shared identity [17], homophily [18], and reciprocity [19]. Building on the premise that social components play an essential role in support provision, our research advances the field by examining social support provision through the lens of social capital theory, which provides a unified framework to understand how network structures generate resources that facilitate supportive behaviors.

2.2. Conceptualizing social support provision: Beyond quantity

This study focuses on informational and emotional supports. The literature on social support presents various types, with Cutrona and Suhr’s [20] taxonomy being the most universally adopted. This categorization delineates five functions of social support: informational, emotional, esteem, network, and tangible support. Within the realm of OSGs, informational and emotional supports emerge as the most common types of social support [21–24]. Informational support encapsulates the provision of advice, facts, and feedback, while emotional support entails expressing care, concern, empathy, and sympathy [20]. Although both types fundamentally aim to bolster individual well-being, they exhibit significant divergences in terms of motivation and mechanism [25,26]. Consequently, investigating the distinct theoretical trajectories that lead to these support behaviors is vital.

Social support provision is defined as the delivery of supportive actions or messages to others [27]. Prior research has predominantly concentrated on the quantitative aspect of social support provision [25], referencing the volume of social support an individual extends to others. Undoubtedly, the quantity of social support represents a crucial dimension in understanding this construct. However, a sole focus on quantity is insufficient to provide a comprehensive perspective on social support, including its origins and implications.

This study endeavors to expand the understanding of social support by incorporating two additional dimensions: quality and timing. The inclusion of quality and timing allows for a more nuanced examination of social support provision, aspects that have been previously overlooked in social support research that employs digital traces. Given that each dimension adds a unique facet to the concept of social support provision, scrutinizing each along with its antecedents elucidates the underlying mechanisms shaping these diverse dimensions of support provision.

The quality of informational support is conceptualized as the uniqueness of information contained within support messages provided by an individual. Within OSGs, members can offer supportive information either by replicating data from other sources or generating their unique or innovative insights. Information that merely duplicates other sources is seen as redundant and tends to hold less value for the recipients of the informational support compared to original insights [28,29]. Consequently, the uniqueness of information emerges as a crucial indicator of the quality of informational support within OSGs.

The quality of emotional support is characterized as the extent to which an emotional message is elaborated and reflects a support seeker’s expressions. According to the person-centeredness framework, the high quality of emotional support explicitly recognizes, elaborates, and investigates a support seeker’s feelings [30]. A message that mirrors a support seeker’s feelings aids them in gaining insight into their own emotions [30]. Furthermore, an expanded message that clarifies and validates a support seeker’s feelings enables them to assess their emotions in a broader context. Therefore, an elaborated message that reflect the support seeker’s expressions characterize the quality aspect of emotional support.

Another vital dimension considered in this study is timing, which pertains to the promptness of support provision. Although asynchronism of OSGs have positive aspects such as convenience for use [18] and the ability to accommodate responses from multiple users [17], empirical evidence reveals that users generally perceive immediate responses more positively than delayed ones [18,31]. Coping with stress is a dynamic process requiring different types of support at different times [32]. People seek social support “when” they need it, making a swift more value than a delayed one, as it better addresses the seeker’s immediate needs. Hence, timing is recognized as the third dimension of support provision.

In sum, this study focuses on the provision of informational and emotional support, and examining three underlying dimensions (quantity, quality, and timing) of each type. Given the distinct value of informational and emotional support, the uniqueness of information represents the quality of informational support, while the level of elaboration and reflection on support seekers characterizes the quality of emotional support. Table 1 presents definitions and examples of informational and emotional support drawn from the study data.

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Table 1. Definitions and examples of informational and emotional support.

https://doi.org/10.1371/journal.pone.0325108.t001

2.3. Social capital theory: A structural perspective to understand social support provision

Studies investigating the precursors of social support provision in OSGs underscore the significance of social and relational perspectives. As discussed earlier, social factors play a crucial role in influencing social support provision [16–18,33,34]. This empirical evidence suggests that understanding the social context within OSGs offers valuable insights into the determinants that either encourage or limit social support provision.

Social capital theory postulates that individuals who are better connected with others tend to prosper [35]. The theory identifies two types of network structures that depict this “better connection,” namely brokerage [36] and closure [3]. Each of these structures generates different forms of social capital. Brokerage facilitates access to non-redundant information [35], while trust is cultivated within closed network structures [3]. As these network structures through their corresponding social capital promote individual’s competence and motivation that are necessary for social support provision [37], they have the potential to translate individual’s social connections into empowered supportive actions.

2.4. Characteristics of brokerage and its relationship with social support provision

Brokerage is conceptualized as a network structure where individuals bridge gaps between groups [35]. Those individuals, referred to as brokers, benefit from their positioning within structural holes that bridge gaps between weakly connected groups. As brokers maintain weak but diversified and non-redundant connections, they gain privileged access to a diverse pool of information that overlaps minimally. This position enables brokers to cultivate intellectual and emotional skills necessary for effective communication across a wide range of contacts [38]. Previous research has shown that brokers demonstrate elevated creativity [39], generate insightful ideas [40], and deliver unique information [28].

In the context of social support, it is predicted that brokerage facilitates the provision of both informational and emotional support. As previously noted, brokers have opportunities to develop intellectual and emotional competencies essential for effective support in both realms. Interacting with diverse individuals allows brokers to broaden their knowledge on a myriad of topics and acquire emotional skills useful for comforting individuals facing various challenges. Competency, or self-efficacy, is a key facilitator of behaviors [41]. With increased competence in informational knowledge and emotional skills, brokers are more likely to provide larger quantities of informational support [7] and emotional support. Furthermore, competence is a vital factor in delivering effective informational [25] and emotional support messages [37]. Therefore, brokers are expected to offer higher quality support in both areas than non-brokers. Moreover, by strategically positioning themselves within their social networks, brokers can efficiently exchange information and resources with others [35]. As a result, they may be better equipped to respond to the needs of their contacts more promptly than those not engaged in brokerage.

H1a-c: A brokerage position occupied by an individual user in an OSG will result in a) greater quantity, b) better quality, and c) quicker timing of informational support provision, compared to a position with less brokerage.

H2a-c: A brokerage position occupied by an individual user in an OSG will result in a) greater quantity, b) better quality, and c) quicker timing of emotional support provision, compared to a position with less brokerage.

2.5. Non-redundant information as social capital mediating brokerage and social support provision

The non-redundant information environment serves as a unique form of social capital that arises from a brokerage structure. As previously noted, a brokerage structure connects individuals from diverse backgrounds through weak ties, thereby facilitating exposure to a variety of non-overlapping information [35]. Although concrete empirical evidence remains sparse, prior research suggests that non-redundant information contributes to the generation of innovative ideas and the enhancement of creativity [42].

In the context of OSGs, the non-redundant information environment underpins the reason brokers can offer more effective informational support. Being embedded in such environments allows brokers to broaden their knowledge on diverse topics [35], which is a critical competency for providing informational support. Brokers are then equipped to offer unique informational support, as their placement in these environments encourages the generation of novel ideas by amalgamating various less overlapping pieces of information [39]. Since they are in a non-redundant information environment [43], brokers can discover or create this unique and valuable information more swiftly, leading to the prompt provision of informational support.

Similarly, a non-redundant information environment also facilitates brokers in delivering more effective emotional support. To offer effective emotional support, individuals need cognitive abilities to recognize others’ emotional and cognitive states and generate comforting messages [37]. Given that non-redundant information environments host a wider pool of information that one can use to develop such cognitive and social perception skills, compared to redundant information environments, they assist brokers in providing larger quantities and higher quality of emotional support promptly. Consequently, a positive relationship exists between brokerage and non-redundant information, and from non-redundant information to the diverse aspects of informational and emotional support provision, suggesting a mediating role of non-redundant information environments.

H3a-c: A non-redundant information environment will mediate the relationship between brokerage and a) the quantity, b) quality, and c) timing of information support provision.

H4a-c A non-redundant information environment will mediate the relationship between brokerage and a) the quantity, b) quality, and c) timing of emotional support provision.

2.6. Characteristics of closure and its relationship with social support provision

Closure represents a type of network structure characterized by strong connections among individuals [44], and strong ties often foster a sense of trust among network members [3]. This trustful environment encourages prosocial behaviors as individuals feel confident that their actions benefiting others will be reciprocated [3]. As members in closed networks are densely and directly connected, closure fosters frequent and direct communication among them, leading to shared values, mutual awareness of needs, and the fluid provision of social help [45].

Within the realm of social support, members embedded in closure are more likely to offer both informational and emotional support compared to those in less closed structures. Typically, closure comprises strong ties that spur a significant motivation for assistance [46]. Individuals connected through strong ties often exchange a wide array of social supports including companionship, minor services, and emotional support [26]. Empirical evidence indicates that people primarily receive social support on social media from close others with whom they share strong ties [47]. Bound by strong ties, members of a closed network are more likely to be motivated to provide both informational and emotional support, as they wish to alleviate any distress experienced by other members. Existing empirical studies validate the role of closure in fostering knowledge transfer and exchange, as well as emotional support [47–49].

Regarding the quality of social support, members in a closure are more likely to offer high-quality informational and emotional support. Despite the traditional notion that strong ties may not facilitate the provision of valuable information due to information redundancy, empirical evidence suggests that people often perceive information as more valuable when it comes from strong ties [50]. This is likely because individuals in a closed network develop mutual understanding and are capable of tailoring messages to fit the recipient’s prior knowledge and needs [51]. Following the same logic, members in closure should provide higher quality emotional support given their enhanced understanding of others’ emotional statuses and needs. Moreover, as members within closure care for others’ well-being and needs [52] and feel motivated to assist [46], closure will likely facilitate the prompt provision of social support when solicited.

H5a-c: A closure position occupied by an individual user in an OSG will result in a) greater quantity, b) better quality, and c) quicker timing of informational support provision, compared to a position with less closure.

H6a-c: A closure position occupied by an individual user in an OSG will result in a) greater quantity, b) better quality, and c) quicker timing of emotional support provision, compared to a position with less closure.

2.7. Trust as social capital mediating closure and social support provision

Trust is the form of social capital that can be derived from closed networks [3]. Within a closed network, members establish close relationships, leading to the development of trust. Trust has been demonstrated to play an important role in facilitating various social interactions, including monetary transactions in e-commerce [53], knowledge sharing in online communities [2], and support seeking [54].

In the contexts of OSGs, trust could facilitate the provision of both informational and emotional social support. Members in a closed network are likely to be more motivated to provide such support, as they trust that their actions will be reciprocated when they themselves need support. Trust also impacts the quality and effectiveness of the support provided, as individuals are more inclined to offer genuine and beneficial assistance when they trust the recipient of their support. In a trusting environment, individuals feel more secure in sharing their emotional experiences [55]. The exchange of such affective self-disclosure can lead to a deeper understanding of each other’s emotional states, reinforcing the trusting relationships and thereby enhancing the quality of both informational and emotional support offered. Furthermore, trust can reinforce social obligations and the sense of responsibility to respond to support requests promptly [3], implying that members in a trustful network are more likely to offer social support in a timely manner. This discussion suggests a mediating role of trust in the relationship between closure and multiple dimensions of both informational and emotional support. Fig 1 illustrates the proposed research model.

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Fig 1. Proposed research model.

https://doi.org/10.1371/journal.pone.0325108.g001

H7a-c: Trust will mediate the relationship between closure and a) the quantity, b) quality, and c) timing of information support provision.

H8a-c: Trust will mediate the relationship between closure and a) the quantity, b) quality, and c) timing of emotional support provision.

The dynamic nature of OSGs with members constantly joining and leaving could play a significant role in how network structures and social capital influence social support provision. In the early stages of an OSG, members often have more opportunities to form close connections and establish trust. It is plausible that during this phase, closed network structures and trust may be more prominent [56], while brokerage structures and non-redundant information could be less prevalent. However, as the community grows and more members join, the dynamics between network structures, social capital, and social support provision may shift. For instance, brokerage positions might increase as new members join, and structural holes can be created amidst the network’s expansion. Consequently, the role of closed network and trust in support provision could be weaker in the later stage compared to the early stage. Understanding how these dynamics change as an OSG moves through different development stages—from early to growth and maturity stages—could provide crucial insights into the mechanism of support provision. Thus, this study proposes the following research question.

RQ1: Will the development stage of OSGs moderate the relationships among network structures, social capital, and social support provision?

3.1. Data collection and research design

Data were collected from a prominent online cancer community in South Korea. The Institutional Review Board (IRB) of Michigan State University in the U.S. approved the data collection with exemption (MSU Study ID: STUDY00003611). The IRB exempted the requirement for informed consent due to the archival nature of the data. Before the researchers accessed the data, each user’s screen name was replaced with a randomly generated six-digit number, and the original screen name was discarded to ensure full anonymity.

The programming language Python was employed to extract 12 years’ worth of data, spanning from August 13, 2007, to November 25, 2019. The data collection took three weeks, from November 26, 2019, to December 10, 2019. The gathered data included anonymized user screen names, user-generated posts and comments, the categories of these posts, the number of views each post received, and timestamps for all content. Data from the first two years (2007 and 2008) and the final year (2019) were excluded due to the community’s initial instability and the incompleteness of the final year’s data, respectively. The remaining data from 2009 to 2018 were employed for analysis.

The ideal research design to assess the proposed research hypotheses would be a panel design that could track the same group of users throughout the study period, from 2009 to 2018. However, due to the volatile nature of online communities, tracking the same set of users over a prolonged period presents significant challenges. Consequently, this study adopted an innovative design inspired by the revolving two-wave panel design utilized in survey research.

As depicted in Fig 2, we generated 20 distinct panel datasets, with two panels per year: spring (January-April) and fall (September-December). Each panel dataset covers a four-month span. For each panel, we collected data in two sequential waves. In the first wave (January-March or September-November), we measured independent variables (brokerage and closure) and mediators (non-redundant information environment and trust). In the second wave (April or December), we measured dependent variables (quantity, quality, and timing of information support and emotional support). Data from May to August is omitted each year to minimize duplication within the panel datasets. While this interval does not entirely eliminate duplication, it serves to refresh the samples by creating a window for new members to join and existing members to dropout.

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Fig 2. Study design.

https://doi.org/10.1371/journal.pone.0325108.g002

This research design carries three methodological advantages. First, the two-wave panel design enables the establishment of a temporal sequence between independent variables, mediators, and dependent variables, thereby enhancing the internal validity of the results. Second, the revolving panel design ensures a sufficient sample size for each panel, boosting the statistical power of the study. Lastly, the temporal order between different panels allows for explicit examination of how hypothesized relationships among variables may evolve over time.

The panel datasets were categorized into early stage (2009–2012), growth stage (2013–2016), and mature stage (2017–2018) with consideration of the community’s growth rate and to secure an adequate sample size for each stage so that we could investigate RQ1.

The target users for the study were selected based on user activity and interaction with other users. S1 Appendix provides more details on sampling strategy. This selection method yielded valid sample sizes of 284 in the early stage, 2,169 in the growth stage, and 2,765 in the mature stage. Fig 3 provides screenshots of the online community to help readers’ understanding of the webpage structure. Fig 4 illustrates the workflow of data collection and processing.

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Fig 3. Screenshots of

(A) community bulletin board and (B) post and comment page.

https://doi.org/10.1371/journal.pone.0325108.g003

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Fig 4. Workflow of data collection and processing.

https://doi.org/10.1371/journal.pone.0325108.g004

3.2. Measurements

3.2.4. Control variable.

Individual post activity (i.e., initiating discussion) was included as a control variable. This activity is quantified by tallying the number of posts a focal individual uploaded during the four months of the study period. To reduce skewness, this control variable was log-transformed. Table 2 provides an overview of the study variables and their operationalizations.

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Table 2. Study variables and operationalizations.

https://doi.org/10.1371/journal.pone.0325108.t002

3.3. Analytic plans

To test the research hypotheses and the research question, we conducted two multigroup path analyses using the R-package lavaan [67]. Initially, we constructed a coefficient-constrained multigroup model to evaluate the research hypotheses. This model assumes that loadings (or coefficients) remain identical across groups (i.e., the early, growth, and mature stages of the community). This approach enables the researcher to estimate the general associations among variables, disregarding the group factor.

To investigate the proposed research question, we constructed a coefficient-free multigroup model and compared it to the coefficient-constrained multigroup model. Unlike the coefficient-constrained model that sets fixed loadings across groups, a coefficient-free multigroup model allows groups to exhibit different coefficients. By comparing the coefficient-free model with the coefficient-constrained model via the chi-square difference test, we can determine whether path effects statistically vary across groups. In essence, the comparison between these two models provides the opportunity to examine whether the paths are moderated by the group factor.

4.1. Descriptive results

The total sample size of the data is 5,218. The sample consists of 3,574 unique users, 73% (n = 2,607) of which appear once and 27% (n = 967) of which appear more than once across panel datasets. On average, the target individuals updated 5 posts (SD = 8.50, median = 3) and 47 comments (SD = 108.39, median = 17) during the four months of the study period. Among uploaded content, 51% of them are support provision, 12% are support seeking, 37% are others (e.g., gratitude expression). Among support-provision content, 48% are information support and 36% are emotional support, which indicates that information and emotional support provision (85%) are the dominant types of social support compared to other types of social support (15%).

Descriptive network statistics of the OSG at different development stages help understand the study context. It is notable that the data for the following descriptive statistics are based on activities from not only the target users but also other members who were active and potentially interacted with target members during the study period. The average network size in the early stage was about 477, and it increased to 2,337 in the growth stage and to 6,947 in the mature stage. Although on average a member’s personal network expanded along with the growth of the community, the expansion did not increase after reaching a certain level. The degree centrality metrics indicate that a member interacted with 7 other members on average in the early stage, and the number expanded to 13 in the growth stage. However, despite the continuing growth, in the mature stage, the degree centrality remained at 12, which is similar to that of the growth stage.

Table 3 provides more detailed statistics of the network metrics along with other network metrics such as brokerage, density, and closure that can provide more information about the context of the OSG across the study panels. Table 4 provides descriptive statistics such as mean, standard deviation, and zero-order correlation of the study variables.

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Table 3. Summary of network statistics across the panel.

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Table 4. Means, standard deviations, and zero-order correlations of variables.

https://doi.org/10.1371/journal.pone.0325108.t004

4.2. Hypotheses testing

The proposed research model fitted to the data (χ²(77) = 359.63, p < .001, CFI = .97, RMSEA = .05, SRMR = .03). The results largely supported the hypotheses suggesting that brokerage facilitates informational support provision via non-redundant information environment, whereas there were mixed findings about the role of brokerage in promoting emotional support provision. In addition, although closure played a restricted role in promoting both informational and emotional support provision, closure facilitated a high quality of emotional support via trust.

H1a, H1b, and H1c examined the direct effect of brokerage on information support provision. Consistent with H1a, individuals provided more information support (β = .25, p < .001) when they were embedded in a brokerage position. Inconsistent with H1b and H1c, brokerage did not directly facilitate the provision of unique information (β = .03, p = .08) and the timing of information support (β = .03, p = .06). Therefore, H1a was supported, whereas H1b and H1c were rejected.

H2a, H2b, and H2c predicted the positive direct effect of brokerage on emotional support provision. Consistent with H2a, individuals provided more emotional support when they were in a higher level of brokerage position (β = .22, p < .001). However, inconsistent with H2b and H2c, brokerage did not have direct effect on the quality (β = −.03, p = .13) and the timing of emotional support provision (β = −.01, p = .52). Therefore, H2a was supported, whereas H2b and H2c were rejected.

H3a, H3b, and H3c examined the mediating role of non-redundant information in informational support provision. Consistent with the hypotheses, a non-redundant information environment mediated the relationships between brokerage and the quantity (β = .06, p < .001), brokerage and the uniqueness (β = .03, p < .001), and brokerage and information support timing (β = .02, p < .001). Therefore, H3a, H3b, and H3c were supported.

H4a, H4b, and H4c concerned the mediating role of non-redundant information environment in emotional support provision. Consistent with H4b and H4c, a non-redundant information environment mediated the impact of brokerage on the quality of emotional support (β = .02, p < .001) and the timing of emotional support (β = .03, p < .001). Inconsistent with H4a, the impact of brokerage on the timing of emotional support was not mediated by a non-redundant information environment (β = −.003, p = .39). Therefore, H4b and H4c were supported and H4a was rejected.

H5a, H5b, and H5c predicted the positive direct effect of closure on informational support provision. Despite the significant result, closure did not have a positive direct impact on the quantity (β = −.02, p < .05), which was inconsistent with H5a. Moreover, inconsistent with H5b and H5c, closure did not have direct impacts on the uniqueness (β = .002, p = .84) and the speed of information support (β = .01, p = .41). Thus, H5a, H5b, and H5c were rejected.

H6a, H6b, and H6c predicted that the positive direct effect of closure on emotional support provision. Consistent with H6a, closure had a direct effect on the quantity of emotional support (β = .03, p < .001). Inconsistent with H6b, closure had a negative impact on the quality of emotional support (β = −.03, p < .05). Moreover, inconsistent with H6c, closure did not affect the speed of emotional support (β = −.01, p = .21). Therefore, H6a was supported and H6b and H6c were rejected.

H7a, H7b, and H7c concerned the mediating role of trust in information support provision. Inconsistent with H7a and H7b, there were negative indirect effects on the quantity (β = −.01, p < .001) and the uniqueness of information support provision (β = −.004, p < .01). Furthermore, inconsistent with H7c, trust did not mediate the relationship between closure and the speed of information support provision (β = −.001, p = .18). Thus, H7a, H7b, and H7c were rejected.

H8a, H8b, and H8c predicted the mediating role of closure in emotional support provision. Consistent with H8b, closure mediated the impact of trust on the quality of emotional support (β = .01, p < .001). Inconsistent with H8a, the impact of closure on the quantity of emotional support was negatively mediated by trust (β = −.01, p < .001). Moreover, inconsistent with H8c, trust did not mediate the relationship between closure and the speed of emotional support (β = .001, p = .22). Thus, H8b was supported and H8a and H8c were rejected. Table 5 provides the summary of the results.

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Table 5. Results of hypotheses testing.

https://doi.org/10.1371/journal.pone.0325108.t005

4.3. Research question testing

RQ1 asks if paths from network structure, social capital, to social support provision differ across the development stages of the OSG. To examine the research question, a coefficient-free multigroup model was compared with a coefficient-constrained multigroup model via the chi-square difference test. The two models had a significant difference such that the fit of a coefficient-free model is better than that of a coefficient-constrained model, indicating that path coefficients are moderated by the development stage of the OSG, χ² difference (62) = 269.38, p < .001. Thus, the relationships between network structure, social capital, and social support provision varied across the early, growth, and mature stages of the community.

Overall, the findings highlight that the roles of brokerage and closure and their social capital in facilitating social support provision are more critical in the later stages than the early stage. For instance, the indirect effect of brokerage via non-redundant information environment on information quantity, uniqueness, and speed were not significant in the early stage whereas these indirect effects were significant in the growth and mature stages. Similarly, the indirect impacts of brokerage via non-redundant information environment on the quality and speed of emotional support provision were not significant in the early stage but were significant in the growth and mature stages.

The roles of closure and trust in promoting information and emotional support were nuanced and complex. As the results of hypotheses suggested, many results were nonsignificant or contradictory to the predictions. Nevertheless, some significant results indicated that closure and trust play important roles in emotional support provision especially in the later stages of OSG. The direct impact of closure on the quantity of emotional support was not significant in the early stage but significant in the later stage. Moreover, the indirect impact of closure via trust on the quality of emotional support was only significant in the growth and mature stages. Table 6 summarizes path coefficients at different stages of the OSG.

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Table 6. Path coefficients at the early, growth, and mature stage of the OSG.

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5.1. Study findings and implications

The findings align with previous studies asserting that individuals in high brokerage positions expand their knowledge and make informational contributions by capitalizing on non-redundant information [42] (H1a–c and H3a–c). These findings support the concept that bridging social connections or interactions empower individuals to access non-duplicative information and promote the circulation of knowledge [35]. While the social support literature has proposed the advantages of OSGs for information support based on the concept of weak ties [17], empirical evidence backing this argument has been sparse, leaving the specific mechanism vague. The findings from this current study clarify why OSGs can be a crucial source for information support. OSGs serve as a useful source of information support because individuals leverage the weak-tie nature of OSGs. By being exposed to a non-redundant information environment, those in brokerage positions are capable of offering more ample, prompt, and valuable information support to community members.

The findings of this study show that brokerage and the associated social capital not only enhance informational support provision but also improve emotional support provision (H2a-c and H4a-c). Previous research has primarily explored the role of brokerage and non-redundant information in the context of informational contributions [28,39,40]. This study is among the first to investigate the role of brokerage and non-redundant information in the context of emotional support. The results of the study back up the claim that an individual’s cognitive ability and social perception are crucial in providing effective emotional support [37], and such cognitive competency can be learned and developed by being embedded in diverse and less redundant information environments.

In contrast to the study hypotheses, the closure structure and trust hinder information support provision (H5a-c and H7a-c). These findings are inconsistent with theories suggesting that closure structures mobilize social assistance with enhanced motivation [45,46]. It seems that the helping motivation derived from social relationships is not an adequate qualification for information support provision. Indeed, relational intimacy does not guarantee informational support provision [68]. Prior empirical studies indicate that relational attributes (e.g., frequent interaction, trust, social identity) do not have a significant impact on informational support provision [25]. It seems that rather than relational closeness or strength, knowledge or cognitive abilities, which increase an individual’s capacity to provide information, could play a more crucial role in informational support provision [25,37]. While individuals in a closure structure may possess strong motivation to help others, they might lack the required abilities or resources to do so, possibly due to their embeddedness in redundant information environments.

Closure facilitates the provision of high-quality emotional support through trust (H8b) rather than having a direct effect on its own (H6b). These results align with prior research suggesting that individuals within trustful relationships effectively fulfill one another’s emotional support needs through compassionate and responsive communication [69]. It appears that individuals who trust their fellow members in OSGs are more likely to provide emotionally responsive and high-quality messages. The quality of supportive messages has been correlated with positive outcomes for the recipients [30], thereby making the identification of factors that enhance the provision of high-quality messages a crucial issue in the field of social support research. While previous studies have identified relational factors as significant influencers of the quality of emotional support [70], this study expands on this body of research by explicitly specifying trust as a key underlying mechanism that allows individuals in close relationships to provide high-quality emotional support. Therefore, fostering trust within online communities may be an effective strategy for improving the quality of emotional support shared among its members.

Although closure and trust play a role in facilitating a higher quality of emotional support, the effect was relatively small. Moreover, many of the proposed research hypotheses concerning the relationships between closure, trust, and emotional support were rejected (H6b, H6c, H8a, and H8c), implying limited effects of closure and trust on emotional support provision. This limited role could be attributed to the nature of OSGs, which largely revolve around weak-tie relationships. As the descriptive statistics of this study indicate, closure is not a prevalent social structure at least within the studied OSG. Given the scale of such communities, where countless members are posting and interacting daily, sustaining long-term interactions with the same group of individuals may be a difficult endeavor [17,18]. Furthermore, the existence of a closed network can be easily threatened by the withdrawal of even a single member. Consequently, maintaining a closure structure over an extended period in OSGs can be highly challenging. The nature of computer-mediated communication environments, which are typically characterized by a lack of social cues and potential delays in responses, may further hinder the establishment of close-knit networks and the development of intimate relationships. Therefore, it is possible that the weak-tie nature of OSGs could render closure structures fragile and less impactful, which in turn could dilute the effects of closure and trust on the various aspects of emotional support.

The findings underscore the importance of considering the unique characteristics and developmental stages of OSGs when assessing the dynamics of network structure, social capital, and support provision (RQ1). Specifically, this study found that as OSGs develop and grow, their networks tend to diversify, characterized by an increase in brokerage and a decrease in closure. This implies that these groups tend to embody the “weak-tie” nature of social relationships more strongly over time. As the size of the network expands, members have increased opportunities to interact with new individuals rather than continuously engaging with the same people. This dynamic enhances the weak-tie nature of OSGs and appears to confer benefits to the community as a whole. In comparison to the early stages of an OSG, the impacts of brokerage and non-redundancy on both informational and emotional support provision are found to be greater in the growth and mature stages. This suggests that the enhanced weak-tie nature of the group amplifies the impact of weak-tie-related structures and social capital on social support.

Interestingly, as the weak-tie network within the OSG becomes more pronounced, the importance of closure and trust—elements rooted in strong-tie relationships—increases, particularly for emotional support provision. During the early stage of the OSG, where members share relatively close relationships, the role of closure and trust in emotional support may have been less pronounced. However, as the OSG expands and welcomes an influx of new members, maintaining strong-tie-based structures becomes increasingly important for amplifying the quantity of emotional support, while trust cultivation enhances the quality of support provided. This underscores the value of nurturing and sustaining strong-tie relationships and trust within the OSG [51], particularly as OSGs continue to grow and reinforce the weak-tie nature of their networks.

5.2. Theoretical and practical contributions

This study offers significant theoretical and practical contributions. It enriches the social capital literature by emphasizing the benefits of distinctly separating social capital from network structures. Despite their conceptual differences, many previous studies have treated social capital as synonymous with network structures [25, 71]. However, recent evidence suggests that network structures such as brokerage should not be used as a proxy for social capital (e.g., access to non-redundant information), given their conceptual and empirical differences [72]. This conceptual reductionism, which conflates network structure with social capital, obstructs our understanding of the theoretical pathway from network structure, through social capital, to social behaviors. The findings of the current study validate that network structures and social capital are distinct entities. By distinguishing these two concepts, we can enhance research by elucidating the theoretical trajectories leading to prosocial behaviors.

This study enhances the social support literature by conceptualizing the provision of social support as a multifaceted concept. As opposed to the development of other perceptual support concepts, the conceptual and operational definitions of behavioral support have seen minimal development. Consequently, most previous studies focus solely on the quantity aspect of social support provision [25]. This limitation can result in neglecting crucial mechanisms of support provision. For instance, had the current study only measured the quantity of support provision, it would have failed to uncover the role of closure and trust in promoting the quality of emotional support. By consolidating the aspects of quantity, quality, and timing—which collectively offer vital behavioral information about support provision—this study yields meaningful insights into social support provision.

Practically, this study encourages community administrators and web designers to devise strategies for enhancing social connections among members, drawing upon theoretical guidance and empirical evidence from social capital research. Given that user interactions are significantly influenced and directed by the functions and services provided by OSGs, administrators and web designers have the power to foster network configurations and social capital. For the longevity of OSGs, it’s essential to strike a balance between weak and strong ties to facilitate both informational and emotional support provisions. However, considering the inherent weak-tie nature of OSGs, these groups may need to introduce features and services that can bolster strong-ties-based network structures (e.g., closure) and social capital (e.g., trust) among members. For instance, they could establish a sub-community system, enabling a small group of members to engage in intensive discussions on specific topics.

5.3. Limitations and future study directions

This study has limitations that pave the way for future research directions. A primary limitation of this study is the focus on a single communication channel (i.e., online support community). Given that people use multiple communication channels for social support exchange [73], this narrow observation may exclude support behaviors occurring outside the community platform. Moreover, as people tend to use different communication channels as their relationship with others develops [74], they may engage in social support exchange via other personal communication channels as their relationships with fellow community members progress. Therefore, future research should incorporate multiple communication channels individuals use for social support exchange to gain a more comprehensive understanding of the role of networks and social capital in support provision.

This research is limited in providing nuanced insights into support provision that differentiate between closely connected group members and more distant connections. Individuals in closure networks may distinguish between members within their immediate social circle and those outside it when providing social support, and patterns of support may differ depending on the recipient. For example, individuals in closure networks may provide greater amounts and higher quality of social support more promptly to members of their inner circles compared to those at the periphery of their networks. This nuanced distinction may explain why this study failed to find significant results for most pathways linking closure and social support. Future research should explore this nuanced approach to fully understand the social mechanisms underlying social support provision.

Finally, this research constructed a social network based on interactions rather than relationships, which limits the generalizability of our findings to relationship-based networks (e.g., closeness or friendship). Although interaction frequency and relational intimacy are related, they are not equivalent. For instance, individuals who interact frequently do not necessarily maintain close relationships, nor does infrequent interaction always indicate relational distance. This implies that brokerage and closure measured in this research could be qualitatively different from those measured through a relationship-based network. Future research should replicate our study using relationship-based social networks where the closeness between individuals is explicitly known.