In collaboration with Macaire Ament, Andrew Lewis, Jason Nguyen, Ryan Tyler, and Chandler Wilson, Spring 2016

When studying social networks and what it means to be connected to others in the world, one area of great interest is the benefits that an individual may reap from knowing others. This is commonly referred to as social capital (Ellison et al., 2011). This study investigates the topic of social capital and other factors associated with it, such as network transitivity and gender. Researchers are interested in understanding if the sex of teammates made a difference in network transitivity and social capital. The study focuses on members of the University of Texas at Dallas Division III Men’s and Women’s Soccer teams. By studying one specific type of group or social network (a sports team), researchers intend to focus the study, and decrease the likelihood of interference from differences in group dynamics or group purpose.

A Review of Research on Social Capital

Social capital can be understood in broad terms by thinking of it as, “the good stuff we get from knowing other people.” There are two types of social capital: bridging, and bonding (Ellison et al., 2011). Bridging social capital is typically associated with weak ties and tends to take the form of exposure to new information (Ellison et al., 2011). In contrast, bonding social capital is associated with strong ties and tends to take the form of emotional support (Ellison et al., 2011). While strong ties are more likely to be part of highly similar networks, Granovetter (1973) explains that weak ties are likely to move in different social circles and will thus have access to different information than close ties. New information that flows from outside a homophilous group may be valuable in certain aspects of life, such as in a professional job search setting.

There is a belief among some student-athletes that when it comes to the job search, “the hours of training, toning and teamwork [are] more beneficial than any internship or job experience on a résumé,” which may lead to the belief that playing for a college sports team provides a  leg-up when searching for employment after graduation (Stark, 2011). This study takes a different approach to the topic of the student-athlete job search. Granovetter (1973) reveals that most people get jobs based off of information from a weak tie. This is an example of bridging social capital in action—exposure to new information and opportunity from someone who is not a close friend. Bridging social capital is associated with weak ties, so the present study aims to examine one aspect of student-athletes’ job search potential by investigating the presence of bridging social capital in their lives. If this study finds trends or gender differences in bridging social capital among the sample participants, athletic departments may be interested in working to bring all athletes up to the same benefit level regarding their job search after graduation.

When considering benefits for the teams studied in this paper, social capital may also have important connections to the overall goals of team performance. Social capital facilitates cooperation within or among groups (Jowett & Chaundy, 2004). Cooperation within a sports team is essential to success in a team sport. This is made clear in Jowett & Chaundy’s (2004) discussion of the impact of task  and social cohesion on sports team performance. They define task cohesion as the degree to which members cooperate to achieve a common performance goal and social cohesion as the degree to which members of a team like each other (Jowett & Chaundy, 2004). While team performance is positively correlated to both task cohesion and social cohesion, social cohesion has a stronger, more positive correlation. As a part of the transitivity measures section, this study asks teammates to rank how close they feel to one another, which provides an opportunity to examine connections between transitivity, social capital, and social cohesion. Although performance outcomes are not tested in this study, it may be useful for future researchers to identify more specific relationships between social cohesion, transitivity, social capital, and performance.

The work of Van Emmerik (2006) on hard and soft forms of social capital is closely tied to social and task cohesion, as well as to bridging and bonding social capital. Van Emmerik (2006) defines two opposing types of social capital that characterize the purposes for which men and women seek relationships. The form of social capital that facilitates among men is considered hard social capital, which involves work role performance and task-related information. This form of social capital is similar to the information gathering aspect of bridging social capital, as well as to Jowett & Chaundy’s (2004) description of task cohesion. On the other hand, the type of social capital that facilitates among women is considered soft social capital. This form of social capital refers to affective support resources, such as emotional support and expressiveness in relationships (Van Emmerik, 2006). Soft social capital has clear parallels to the emotional support aspect of bonding social capital, as well as to Jowett & Chaundy’s (2004) description of social cohesion. As a result of these parallels, the present study may reflect Van Emmerik’s (2006) work by showing differences in bridging and bonding social capital, with women being expected to exhibit more bonding social capital while men exhibit more bridging social capital.

In order to further examine the relationships between social capital, gender, and transitivity, the following study explores the questions:

RQ1: Do male and female teams differ on  team bridging and bonding social capital?

RQ2: Do male and female teams differ on campus bridging and bonding social capital?

RQ3: Is team transitivity related to team bridging and team bonding social capital

RQ4: Is team transitivity related to campus bridging and campus bonding social capital?

The results were analyzed and applied in consideration of the generalizability to a greater context of social networks.

Method

A cross-sectional, pen and paper survey of the men’s and women’s soccer teams was conducted in order to explore relationships between gender, team transitivity, and social capital. The participants were N = 47 undergraduate students, 61.2% of whom were male and 38.8% of whom were female. The racial breakdown of the sample was 73.5% White/Caucasian, 2% Black/African American, 12.2% Hispanic/Latino, 2% Asian/Middle Eastern, and 10.2% multiracial. The age of participants ranged from 18 to 22, averaging 19.86 years of age. The average amount of time participants had spent on the team was 1.67 years.

The survey asked participants questions regarding bridging and bonding social capital, both on their team and on the UT Dallas campus. Each survey consisted of four parts: Likert scale measures of bridging social capital (for campus/team), Likert scale measures of bonding social capital (for campus/team), demographic information, and a transitivity ranking exercise, which provided participants with a team roster and asked them to rate their closeness to each teammate on a scale of 1 (just teammates) to 3 (close friends). Bridging and bonding social capital measures were adapted from an earlier research project facilitated by Dr. Kristin Drogos. The bridging social capital sections included statements like, “I feel I am a part of the team/UTD community,” while bonding measures were similar to, “There are several people on my campus/team I trust to solve my problems.” The women’s soccer team completed their surveys in an open area, without the presence of their coach. The men’s soccer team completed their surveys in a locker room, with their coach present. All participants were informed of their option not to participate and were provided instructions that protected the identity of those who did and did not participate in the research.

Results

Research Question (1) investigated gender differences in team bridging and bonding social capital scores. An independent samples t-test was used to find differences between male and female participants’ bridging and bonding social capital scores within their teams. There was no significant difference between the male participants team bridging scores (M = 4.11, SD = 0.625) and female participants team bridging scores (M = 4.32, SD = 0.435); t(47) = -1.304, p=0.199). There was also no significant difference between the male participants team bonding scores (M = 3.86, SD = 0.679) and female participants team bridging scores (M = 3.96, SD = 0.726); t(47) = -0.479, p=0.634).

Research Question (2) investigated gender differences in UT Dallas campus bridging and bonding social capital scores. An independent samples t-test was used to find differences between male and female participants’ bridging and bonding social capital scores within the UT Dallas campus. There was a significant difference between the male participants campus bridging scores (M = 3.49, SD = 0.797) and female participants campus bridging scores (M = 3.99, SD = 0.392); t(47) = -2.562, p=0.014). Females had higher average campus bridging social capital than males. There was no significant difference between the male participants campus bonding scores (M = 3.53, SD = 0.573) and female participants campus bonding scores (M = 3.47, SD = 0.488); t(47) = 0.348, p=0.730).

Research Question (3) investigated potential relationships between gender and network transitivity scores. An independent samples t-test was used to find differences between male and female participants’ team transitivity scores. No significant differences were found between male transitivity scores (M = 1.98, SD = 0.424) and female transitivity scores (M = 1.96, SD = 0.224); t(47) = 0.185, p=0.854).

Research Question (4) investigated potential relationships between transitivity and social capital. In order to test the relationship between transitivity and social capital, a simple linear regression  was conducted. A significant regression equation was found such that team network transitivity predicted campus-wide bonding social capital (β = .41, p < .01).

The transitivity exercise was also used to create social network analyses with a software called SocNetV. The nodes (people in the network) are organized by the number of connections it takes to get to each other node, node size is based on the number of inbound ties (number of people who listed a connection to that node).

The nodes are classified as follows:

– Circles are freshmen
– Squares are sophomores
– Diamonds are juniors
– Red is forwards
– Green is defenders
– Yellow is midfielders
– Blue is goalkeepers

The ties are marked as follows:

– Thin black lines are a transitivity ranking of 1
– Pink lines are a transitivity ranking of 2
– Thick black lines are a transitivity ranking of 3

Social Network Analysis for Women’s Soccer
Social Network Analysis for Men’s Soccer

Discussion

Contrary to previous research, findings showed no significant differences in gender regarding team bridging or team bonding social capital scores. Females, however, had higher campus bridging social capital than males.  This contradicts some of the gender differences that were discussed in previous literature. The finding that female athletes have more weak ties in a university setting may be a reflection of other recent research into social capital among student athletes, which showed female college athletes tending to have more ties, higher quality ties, greater investment in their ties, and more positive school affiliation (Clopton, 2012).

One of the major benefits of weak ties and bridging social capital comes in the form of information about new jobs and opportunities. Discovering a difference between the average bridging social capital benefits that male and female athletes receive as part of UT Dallas suggests that male athletes may have more limited exposure to information about new opportunities or ideas than female athletes. Since many collegiate athletes anticipate better job prospects as one benefit of college athletics, further research into how best to leverage bridging social capital benefits for the men’s teams might be in order. Based off of the finding that transitivity scores are positively related to average UT Dallas bridging social capital, increasing male athletes’ feelings of connectedness to their teammates could be a solution. However, since results showed no significant difference between male and female teams’ transitivity scores, this may not be the full root of the gender difference in bridging UT Dallas social capital. Perhaps men are making the same number of weak ties on campus, but are failing to maintain them after the class or project that initiated that tie ends.

In entering higher education, emerging adults are encouraged to socialize, make friends, and particularly to join student organizations on campus in order to maximize bridging and bonding social capital and the expansion of their social networks. The positive relationship recorded in this study between transitivity and campus social capital supports this practice. While only athletic teams were investigated here, it stands to reason that this result might play out for other types of clubs and groups on campus as well. Involvement in a school-affiliated group, especially a sports team that promotes a high level of school pride or a group that is deeply embedded into campus life, may mean that an individual is more likely to gain more connections on campus and thus, increase their bridging and bonding social capital.

Further research to determine whether or not student athletes have more or less UT Dallas based social capital than the rest of the student body would allow for a deeper understanding of the true social benefits of playing a college sport. Also, now that this study has established a relationship between transitivity and social capital, additional research into the link between social cohesion and these factors could provide insight regarding ways to improve team performance.


References

Clopton, A. W. (2012). Social Capital Gender, and the Student Athlete. Group Dynamics: Theory, Research, and Practice, 16(4), 272-288. DOI: 10.1037/a0028376.

Ellison, N. B., Lampe, C., Steinfield, C., & Vitak, J. (2011). With A Little Help From My Friends: How Social Network Sites Affect Social Capital Processes. In A Networked Self, edited by Z. Papacharissi, 124-145. New York: Routledge.

Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 1360-1380. DOI: 10.1086/225469.

Jowett, S., & Chaundy, V. (2004). An Investigation Into the Impact of Coach Leadership and Coach-Athlete Relationship on Group Cohesion. Group Dynamics: Theory, Research, and Practice, 8(4), 302. DOI: 10.1037/1089-2699.8.4.302.

Stark, S. (2011). “College athletes suffer the greatest injustice from NCAA.” USA Today College, August 28. Accessed October 7, 2011. http://college.usatoday.com/2011/08/28/college-athletes-suffer-the-greatest-injustice-from-ncaa/

Van Emmerik, I. J. H. (2006). Gender differences in the creation of different types of social capital: A multilevel study. Social Networks, 28, 24-37. DOI: 10.1016/j.socnet.2005.04.002.