Mixed Methods Social Network Analysis Research Articles

Governance of the wildlife trade and the prevention of emerging zoonoses: a mixed methods network analysis of transnational organisations, silos, and power dynamics

IntroductionThe wildlife trade is an important arena for intervention in the prevention of emerging zoonoses, and leading organisations have advocated for more collaborative, multi-sectoral approaches to governance in this area. The aim of this study is to characterise the structure and function of the network of transnational organisations that interact around the governance of wildlife trade for the prevention of emerging zoonoses, and to assess these network characteristics in terms of how they might support or undermine progress on these issues.MethodsThis study used a mixed methods social network analysis of transnational organisations. Data were collected between May 2021 and September 2022. Participants were representatives of transnational organisations involved in the governance of wildlife trade and the prevention of emerging zoonoses. An initial seed sample of participants was purposively recruited through professional networks, and snowball sampling was used to identify additional participants. Quantitative data were collected through an online network survey. Measures of centrality (degree, closeness, and betweenness) were calculated and the network’s largest clique was identified and characterised. To understand the extent to which organisations were connected across sectors, homophily by sector was assessed using exponential random graph modelling. Qualitative data were collected through semi-structured interviews. The findings from the quantitative analysis informed the focus of the qualitative analysis. Qualitative data were explored using thematic analysis.ResultsThirty-seven participants completed the network survey and 17 key informants participated in semi-structured interviews. A total of 69 organisations were identified as belonging to this network. Organisations spanned the animal, human, and environmental health sectors, among others including trade, food and agriculture, and crime. Organisation types included inter-governmental organisations, non-governmental organisations, treaty secretariats, research institutions, and network organisations. Participants emphasised the highly inter-sectoral nature of this topic and the importance of inter-sectoral work, and connections were present across existing sectors. However, there were many barriers to effective interaction, particularly conflicting goals and agendas. Power dynamics also shaped relationships between actors, with the human health sector seen as better resourced and more influential, despite having historically lower engagement than the environmental and animal health sectors around the wildlife trade and its role in emerging zoonoses.ConclusionThe network of transnational organisations focused on the governance of wildlife trade and the prevention of emerging zoonoses is highly multi-sectoral, but despite progress catalysed by the COVID-19 pandemic, barriers still exist for inter-sectoral interaction and coordination. A One Health approach to governance at this level, which has gained traction throughout the COVID-19 pandemic, was shared as a promising mechanism to support a balancing of roles and agendas in this space. However, this must involve agreement around equity, priorities, and clear goal setting to support effective action.

Peer technical support in preservice teacher education: A mixed methods social network analysis and phenomenological study to understand relative expertise

Peer technical support in preservice teacher education: A mixed methods social network analysis and phenomenological study to understand relative expertise

How do teachers exercise relational agency for supporting migrant students within social networks in schools from Scotland, Finland, and Sweden?

This study examines how teachers exercise relational agency - working flexibly with other actors in their social networks to support migrant students. Teachers and other staff members from 7 schools in Scotland, Finland and Sweden participated in social network surveys (n = 1116), online logs (n = 275) and interviews (n = 82). A mixed-method social network analysis shows how networks facilitate relational agency as teachers reach out to others to mobilise resources and tacit knowledge within their school communities. The findings point to the critical role of professional collaboration and suggest that social networks shape how teachers work with specialists to support migrant students.

THE LONELINESS OF LOW-INCOME OLDER ADULTS IN A FEDERAL VOLUNTEERING PROGRAM: A MIXED-METHOD NETWORK PERSPECTIVE

Abstract Volunteering is considered an important way to prevent and address loneliness for community-living older adults by fostering social interactions. However, some social network studies conducted outside of the volunteering context suggest that increased interactions among lonely individuals can elevate network members’ loneliness through the co-rumination of negative emotions. To understand how and why interactions among older volunteers might protect against loneliness, this study conducted a concurrent mixed-method social network analysis among older volunteers within the Senior Companion Program (SCP) in Columbus, Ohio. These volunteers are 55 years or older, at or below 200% of the federal poverty line, and culturally/linguistically diverse. Qualitative and quantitative data were collected using focus groups and surveys respectively during an SCP monthly in-service training, N=41. A linear network autocorrelation model (LNAM) was constructed to quantify how individuals’ loneliness was correlated in SCP. A grounded theory approach informed the qualitative analysis. Mixed-method integration was conducted through a joint display table. LNAM results on the covariates were consistent with previous loneliness studies on diverse older adults. Furthermore, the negative network autocorrelation indicated that less lonely volunteers tended to interact with lonelier volunteers (ρ= -0.06, p< 0.05). Qualitative results also supported the aforementioned socialization pattern suggestive of altruistic motivations. In other words, the altruistic tendency to interact with other volunteers differing in loneliness may be an important pathway by which volunteering addresses loneliness. Future research shall further examine the mechanism between volunteering and older adults’ psychosocial well-being. Findings have implications for maximizing the health and social benefits of volunteering.

A Mixed-Method Social Network Analysis of Low-Income Diverse Older Volunteers.

Although volunteering has been associated with numerous social benefits for diverse older adults, there is little information on how they establish relationships within a multicultural volunteering program outside of their co-ethnic communities. This convergent mixed-method social network study adopts the bonding and bridging social capital theory to explore the structures and dynamics of social interactions within a multicultural volunteer program. Low-income Russian, Khmer, Somali, Nepali, and English-speaking older volunteers in the Senior Companions Program (SCP) in a Midwest metropolitan (N = 83) participated in the surveys and focus groups. Homophily coefficients (r) show that the SCP volunteers mostly interacted with people who identified with the same nationality (r = .86), race (r = .87), and gender (r = .50). Qualitative results suggested that volunteers strengthened their social networks through within-cultural social bonding while appreciating opportunities for cross-cultural social bridging. Compared with within-cultural social bonding, cross-cultural social bridging in multicultural volunteer programs require intentional facilitation, resources, and organizational commitment.

#Answerusyoutube: predatory influencers and cross-platform insulation

ABSTRACT In the summer of 2020, dozens of high-profile influencers in videogaming entertainment were accused of sexual harassment and predatory behavior. Among them, popular gaming YouTuber Craig Thompson (username Mini Ladd) confessed on Twitter to sexting minors but resumed uploading content to his YouTube channel one month later, resulting in public outcry. Thompson’s return to YouTube, as a case study, illustrates how predatory influencers can manipulate technical affordances across social media platforms to insulate themselves from accountability and maintain their revenue and audience. Drawing on data scraped from Twitter (34k tweets) and YouTube (62k comments and video network data), this article uses a mixed-methods social network analysis (Burgess & Matamoros-Fernández, 2016) to map the public effort to deplatform Mini Ladd. This case study explores issues of cross-platform insulation and audience manipulation by demonstrating how a predatory influencer: 1) censored keywords in his comments to obfuscate criticism; 2) optimized YouTube’s video algorithms to avoid references to his scandal; and 3) upheld harassment towards his young fanbase. Ultimately, I argue that YouTube’s policies are ill-equipped to manage the networked practices of predatory influencers and that the platform’s reliance on morally motivated networked harassment (Marwick, 2021) as a substitute is troubling and ineffective.

How Expert and Inexpert Instructors Talk about Teaching

Using mixed-method social network analysis, we explored the discussions happening between instructors within a teaching-related network and how instructional expertise correlated with the content of those discussions. Instructional expertise, defined by the extent to which effective teaching practices were implemented, was measured for 82 faculty teaching at a Midwestern research university in the USA using the Faculty Inventory of Methods and Practices Associated with Competent Teaching (F-IMPACT). Eight instructors from this population were interviewed after being selected from a stratified random sample having varied disciplines, positions, years of teaching experience, number of network alters, and quartile F-IMPACT score. Network Canvas was used to design, capture, and export network data during the interview process, and a deductive qualitative analysis approach was used for coding and analysis. In general, expert instructors had larger networks that also consisted of expert alters and greater frequency of discussions throughout the semester (both formal and informal) and participated in discussions centered around best practices and education research. Inexpert instructors had smaller teaching networks that consisted of other inexpert instructors, lower frequency of interactions, and had discussions that centered around sharing course-specific, surface-level advice.

Connecting for Care: a protocol for a mixed-method social network analysis to advance knowledge translation in the field of child development and rehabilitation

BackgroundConnections between individuals and organizations can impact knowledge translation (KT). This finding has led to growing interest in the study of social networks as drivers of KT. Social networks are formed by the patterns of relationships or connections generated through interactions. These connections can be studied using social network analysis (SNA) methodologies. The relatively small yet diverse community in the field of child development and rehabilitation (CD&R) in Canada offers an ideal case study for applying SNA. The purposes of this work are to (1) quantify and map the structure of Canadian CD&R KT networks among four groups: families, health care providers, KT support personnel, and researchers; (2) explore participant perspectives of the network structure and of KT barriers and facilitators within it; and (3) generate recommendations to improve KT capacity within and between groups. Aligning with the principles of integrated KT, we have assembled a national team whose members contribute throughout the research and KT process, with representation from the four participant groups.MethodsA sequential, explanatory mixed-method study, within the bounds of a national case study in the field of CD&R. Objective 1: A national SNA survey of family members with advocacy/partnership experience, health care providers, KT support personnel, and researchers, paired with an anonymous survey for family member without partnership experience, will gather data to describe the KT networks within and between groups and identify barriers and facilitators of network connections. Objective 2: Purposive sampling from Phase 1 will identify semi-structured interview participants with whom to examine conventional and network-driven KT barriers, facilitators, and mitigating strategies. Objective 3: Intervention mapping and a Delphi process will generate recommendations for network and conventional interventions to strengthen the network and facilitate KT.DiscussionThis study will integrate network and KT theory in mapping the structure of the CD&R KT network, enhance our understanding of conventional and network-focused KT barriers and facilitators, and provide recommendations to strengthen KT networks. Recommendations can be applied and tested within the field of CD&R to improve KT, with the aim of ensuring children achieve the best health outcomes possible through timely access to effective healthcare.

Developing Social Capital through School-Based Collaborations: A Mixed Methods Social Network Analysis

Collaboration has become an important way for organizations to leverage human resources to create shared organizational goals. Schools, as organizations, thrive on positive collegial partnerships among educators, with effective educator collaborations linked to improved school effectiveness and student outcomes. However, not all collaborations are successful. The current study draws heavily from Coleman’s (1988) social capital framework to understand with whom educators choose to interact and how patterns of interaction facilitate educators’ social capital development. Using an equal status, sequential mixed methods design, K–12 educators’ interview and survey data were iteratively analyzed to explore how educators describe their school-based collaborations, how collaborations reveal distinct social network structures, and how school-based collaborations and network structures lead to educators’ social capital. Findings illuminated four distinct profiles of collaboration that emerged as educators described their school-based collaboration, which were linked to different social network structures and qualities of social capital. These results can be used to inform professional development practices for school administrators and human resources teams through consideration of profiles that may inform responsive school-based collaborations. We discuss additional implications for educator hiring and retention as well as policy around PK–12 teacher standards.

The role of social networks in prognostic understanding of older adults with advanced cancer

ObjectivesExplore how older patients utilize their social networks to inform prognostic understanding. MethodsIn a pilot study of adults (≥65 years old) with advanced cancer, 16 patients completed surveys, social network maps, and semi-structured interviews exploring with whom they preferred to communicate about their illness. Interviews were analyzed using open-coding, and codes were categorized into emergent themes. Social network maps and themes were analyzed via mixed-methods social network analysis (MMSNA). Three case examples with diverse network characteristics and communication patterns were selected for further analysis. ResultsThree overarching themes (i.e., prognostic understanding, social support, and therapeutic alliance) revealed that patients’ prognostic understanding was strongly influenced by the quality of the social support patients perceived from members of their social networks. Patients demonstrated prognostic understanding when they reported close relationships and open communication with their network members. Case examples revealed some ways that patients sought information and had better sense of their prognosis when they had supportive social networks. ConclusionFindings illustrate how understanding social networks may provide information on how older adults with cancer seek, share, and process prognostic information.

A Mixed Methods Social Network Analysis of San Diego Law Enforcement Task Forces and Agencies

The San Diego area has a long reputation as a highly networked, cooperative, and task force-oriented law enforcement region. Measuring and understanding how this region achieves its networked state could assist other regions in improving law enforcement functions. This article uses social network analysis to qualitatively and quantitatively map the network of law enforcement agency task forces in the San Diego County region. The analysis first provides an inventory and description of San Diego area law enforcement task forces and participating agencies, then analyzes the structure of the regional network. The analysis identified 33 law enforcement investigative task forces supported by 84 law enforcement and participating agencies in the San Diego area. These comprise a relatively dense network with a well-connected core of primarily federal and local agencies, with the Federal Bureau of Investigation, Drug Enforcement Administration, and Immigration and Customs Enforcement’s Homeland Security Investigations being the most central federal agencies, and the San Diego County District Attorney’s Office and Sheriff’s Department, as well as San Diego, National City, and Chula Vista police departments as the most central local agencies. State agencies were less central but included the California Department of Justice and the California Highway Patrol in the top 10 agencies for centrality, depending on the metric. The network mapping in this article provides a baseline for a highly connected task force region that will allow future comparison with other regions and similarly situated cities along the US-Mexico border and beyond. Policy recommendations based on network theory are provided.

The potential of mixed-method social network analysis for studying interaction between agency and structure in education

ABSTRACT This article discusses the potential of mixed-method social network analysis (MMSNA) as a methodology for designing and conducting studies that address questions of interplay between human agency and social structures in educational settings. First, we discuss a rationale for using MMSNA referring to the theoretical calls for better understanding the role of agency in network structures. Next, we discuss examples of studies that illustrate how MMSNA has been applied to investigate (a) the role of agency in social network formation and (b) how social networks facilitate actors’ agency in educational processes. Finally, we outline a guide for how to use MMSNA and consider its potential for future studies of interactions between agency and structures in educational settings.

Integrating Mixed Methods Social Network Analysis to Assess Community-Academic Partnerships.

Community-academic partnerships (CAPs) in public health are increasingly utilized to integrate community voice into decision-making processes of health-related interventions, programs, and practice. However, community partners' collaboration experiences remain understated in the literature. Thus, there is a need to further advance methodological approaches that examine the effectiveness of CAPs, while also highlighting community voice to, ultimately, improve public health outcomes. (1) To demonstrate how a practical approach to mixed methods social network analysis (MMSNA) can highlight power dynamics in community health partnerships and use MMSNA data to build relationships across stake-holders for systems change effortsMethods: MMSNA was used to examine a CAP focused on public health equity in a Midwest region. The project applied a sequential mixed methods design (QUAN → QUAL) with a network survey and individual semi-structured interviews. Both data strands served the function of expansion, where quantitative data identified what relationships existed in the network, level of activity, and factors for motivations, providing breadth of collaboration. Qualitative data further elaborated on how partners perceived these experiences, providing depth and contextualizing quantitative results. Systems level approaches must be applied to capture broader contexts (e.g., community, interpersonal, and individual) surrounding community health partnerships. The use of MMSNA maximizes benefits from a systems methodology-social network analysis-with qualitative interviews that allow for the critical assessment of network structure and community centered perspectives. Community health partnerships are encouraged to utilize this approach in order to deliver more sustainable public health efforts centered on the community that is directly impacted.

Beyond the Manuscript: Integrating Mixed Methods Social Network Analysis to Assess Community Academic Partnerships

Beyond the Manuscript: Integrating Mixed Methods Social Network Analysis to Assess Community Academic Partnerships

Cohort-Based Education and Other Factors Related to Student Peer Relationships: A Mixed Methods Social Network Analysis

Graduate students face a variety of stressors that relate to poor academic performance, lower completion rates, and high rates of depressive symptoms, anxiety, and stress. Student peers provide supports for coping with these stressors and succeeding academically. However, graduate students may find it difficult to form relationships with their peers. This mixed method social network analysis (MMSNA) examines graduate student perceptions of their peer relationships and the factors associated with peer friendships in a program that placed students in cohorts for the first semester of a two-year Master of Social Work program. Findings from three student focus groups include four main themes related to the cohort system and the tendency for students to gravitate to others who were similar to them (i.e., homophily). Focus group findings informed model specification for a curved exponential family model of student friendships at the end of the third semester of the program (N = 70) that identified correlates of student friendships including statistically significant direct and homophily effects for age, gender, and race/ethnicity. First-semester relationships and shared classes in subsequent semesters also increased the likelihood of friendships in the third semester. Findings emphasize the value of cohorts and a diverse student body for peer relationships.

"GO BACK IN YOUR FETUS CAVE": HOW PREDATORY INFLUENCERS MANIPULATE AUDIENCES THROUGH PLATFORM RETREATS

In the summer of 2020, dozens of high-profile influencers in videogaming entertainment were accused of sexual harassment and predatory behavior. Among these, popular gaming YouTuber Craig Thompson (username 'Mini Ladd') confessed on Twitter to grooming minors but resumed uploading content to his YouTube channel one month later, resulting in public outcry. Thompson’s return to YouTube provides a case study in how predatory influencers can manipulate affordances across platforms, especially on YouTube, to insulate themselves from accountability and maintain their platform. Using scraped data from Twitter (34k tweets) and YouTube (62k comments and video network data), this article uses a mixed-methods social network analysis (Burgess and Matamoros-Fernández 2016) to map the public effort to deplatform Mini Ladd. This case study raises questions about cross-platform insulation and audience manipulation, by demonstrating how a predatory influencer 1) censored keywords in his comments to obfuscate criticism 2) gamed YouTube’s video algorithms to avoid references to his scandal and 3) redirected harassment onto his own fanbase. Ultimately, I argue that predatory influencers manipulate YouTube’s platform affordances to insulate themselves from accountability in the absence of moderation.

‘It’s not 9 to 5 recovery’: the role of a recovery community in producing social bonds that support recovery

Aim To understand how the social networks of a new recovery community can help sustain recovery, focusing on processes of social identity change, in the context of the wider UK recovery movement. Methods A cross-sectional, mixed-methods social network analysis (SNA) of ego-network sociograms to map network transitions, using retrospective measures. Ten men were recruited from a peer-worker programme, in the South Ayrshire Alcohol and Drug Partnership (ADP), West of Scotland. Network measures were compared between two timepoints, just prior to current recovery and the present time. Measures included size and density, closeness of members, and their positive or negative influence, proportion of alcohol and other drug (AOD) using and recovery peers, and extent of separate subgroups. These were complemented with qualitative interview data. Findings There was a significant transition in network composition, with the replacing of AOD-using peers with recovery peers and a broader transformation from relationships being framed as negative to positive. However, there was no significant transition in network structure, with AOD-using and recovery networks both consisting of strong ties and a similar density of connections between people in the networks. Conclusions The transition in network composition between pre-recovery and the present indicates a different set of social influences, while the similarities in network structure indicate that the recovery network replaced the role of the using network in providing close bonds. This helped reduce social isolation experienced in early-recovery and provided a pathway into more structured opportunities for volunteering and employment.

Understanding connectivity: The parallax and disruptive-productive effects of mixed methods social network analysis in occupational science

ABSTRACT This article introduces social network analysis (SNA), a theoretical perspective accompanied by a set of methodologies, to occupational science. The convergence of SNA and occupational science is timely for both fields. By providing methodological approaches that flesh out a structural view of social networks, SNA measurements and mathematical terminology can effectively bridge the complexity of diverse interpretive frameworks used to understand occupational engagement and other constructs for humans as socially occupied beings. By focusing attention on the relationship of occupations to connectivity between agents, occupational science can make significant contributions to the ways in which the mattering or meaning of what people do with others nurtures the development and sustainability of social networks. We provide a brief history and roots of SNA in naturalistic observation, current terminology, and four widely used SNA research designs: egocentric, sociometric, sequenced, and two-mode. Drawing examples from our decade-long journey using SNA with narrative phenomenological conceptual frameworks, we illustrate how we used SNA with experience-near ethnographies to meet different objectives. In the discussion, we reflect on the parallax view created by the synergies between the disciplines and how the disruptive-productive effects that occur with mixing narrative phenomenology and SNA methods could address (mutual) methodological gaps that have seemingly limited conceptual development in the social sciences.

Activate, collaborate, participate: The network revolutions of riot grrrl-affiliated music worlds

Social networks act as a metaphor for discussion about many historical and contemporary music worlds. Much of the literature on feminist music movements like riot grrrl, ladyfest and Girls Rock camps conceptualize collective action and participation in network terms. However, in doing so, the approach is almost exclusively qualitative. Individuals tie movements, collectives and organizations together and help their cultural spread across cities and countries. Yet individuals can also cause ruptures in networks that may lead to their collapse or fracturing. This article uses mixed-methods social network analysis (SNA) to unpack the structure, development and impact of a riot grrrl-associated music network across geographical space and time. By investigating the strong ties of shared band membership and playing together, the centrality of key bands and musicians across overlapping music movements associated with riot grrrl are explored at micro, meso and macro levels of network interaction. The ability to visualize music collaboration networks allows us to see patterns and connections that may not have been previously apparent. Whilst there is a small but growing body of work on punk using SNA methods, these have overwhelmingly been male dominated. This is the first formal network application on punk-inspired feminist music worlds that redresses the gender imbalance.

Linking Quantitative and Qualitative Network Approaches: A Review of Mixed Methods Social Network Analysis in Education Research

Social network analysis (SNA) is becoming a prevalent method in education research and practice. But criticism has been voiced against the heavy reliance on quantification within SNA. Recent work suggests combining quantitative and qualitative approaches in SNA—mixed methods social network analysis (MMSNA)—as a remedy. MMSNA is helpful for addressing research questions related to the formal or structural side of relationships and networks, but it also attends to more qualitative questions such as the meaning of interactions or the variability of social relationships. In this chapter, we describe how researchers have applied and presented MMSNA in publications from the perspective of general mixed methods research. Based on a systematic review, we summarize the different applications within the field of education and learning research, point to potential shortcomings of the methods and its presentation, and develop an agenda to support researchers in conducting future MMSNA research.