Social Network Analysis (SNA) for Community Research Training Course

Research & Data Analysis

Social Network Analysis (SNA) for Community Research Training Course offers an in-depth exploration into the application of SNA to map, measure, and visualize the relationships that shape communities.

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Social Network Analysis (SNA) for Community Research Training Course

Course Overview

Social Network Analysis (SNA) for Community Research Training Course

Introduction

In today’s hyper-connected world, Social Network Analysis (SNA) has emerged as a powerful tool for community research, public policy, and grassroots interventions. Social Network Analysis (SNA) for Community Research Training Course offers an in-depth exploration into the application of SNA to map, measure, and visualize the relationships that shape communities. By understanding the structure and dynamics of social networks, community researchers, data analysts, and social scientists can uncover hidden influencers, track information flows, and design data-driven interventions. The course is tailored for both beginners and experienced researchers seeking to amplify the impact of their work through network-based insights.

Leveraging cutting-edge analytics, data visualization, and community engagement techniques, this course equips participants with practical skills in software like Gephi, UCINET, and Python-based tools. Real-world case studies provide a foundation for applying SNA in contexts such as health communication, disaster resilience, youth empowerment, and stakeholder mapping. Whether you're involved in social innovation, academic research, nonprofit work, or civic technology, this course will help you translate network data into actionable community change strategies.

Course Objectives:

  1. Understand core principles of Social Network Analysis (SNA)
  2. Apply SNA tools for community-based research
  3. Analyze network structures and identify key actors
  4. Utilize Gephi and UCINET for visualizing social data
  5. Explore centrality, cohesion, and influence metrics
  6. Conduct stakeholder analysis through SNA
  7. Map information flow and social capital distribution
  8. Leverage SNA for health and development interventions
  9. Integrate SNA into mixed-methods research designs
  10. Evaluate online and offline network behaviors
  11. Use Python for automated social network mapping
  12. Create data-informed community engagement strategies
  13. Develop actionable insights for policy and advocacy

Target Audiences

  1. Community development practitioners
  2. Social science researchers
  3. NGO and nonprofit workers
  4. Urban planners and policy analysts
  5. Public health professionals
  6. Civic tech and data activists
  7. Academic faculty and graduate students
  8. International development consultants

Course Duration: 5 days

Course Modules

Module 1: Introduction to Social Network Analysis

  • Definition and evolution of SNA
  • Core concepts: nodes, ties, density
  • Types of social networks
  • Applications in community settings
  • Tools overview: Gephi, UCINET
  • Case Study: Mapping informal communication in slum communities

Module 2: Data Collection for SNA

  • Qualitative and quantitative methods
  • Designing network surveys
  • Ethical considerations in SNA
  • Using digital trace data (e.g., social media)
  • Cleaning and formatting data for analysis
  • Case Study: Data collection for youth-led networks in Nairobi

Module 3: Network Metrics and Interpretation

  • Centrality (degree, betweenness, closeness)
  • Cohesion and clustering
  • Network density and fragmentation
  • Structural holes and bridging
  • Interpreting real-world meaning
  • Case Study: Identifying influencers in a vaccination campaign

Module 4: Network Visualization Techniques

  1. Principles of effective network visualization
  2. Gephi interface and layout algorithms
  3. Aesthetic customization and export
  4. Color-coding nodes by attributes
  5. Animating network evolution over time
  6. Case Study: Visualizing the spread of misinformation

Module 5: Software Tools: Gephi, UCINET, Python

  1. Gephi workflow for beginners
  2. UCINET for matrix-based analysis
  3. Scripting in Python with NetworkX
  4. Comparing tool outputs
  5. Tips for large network datasets
  6. Case Study: Cross-platform analysis of refugee support networks

Module 6: SNA in Community Health and Development

  • Using SNA for behavioral health campaigns
  • Mapping disease transmission networks
  • Identifying gatekeepers in health communication
  • Social support and recovery networks
  • Measuring intervention impact via network change
  • Case Study: HIV prevention networks in rural Kenya

Module 7: Policy and Advocacy Applications of SNA

  • Mapping power relations and influence
  • Identifying marginalized actors
  • Coalition-building through networks
  • Integrating SNA in policy briefs
  • Leveraging findings for advocacy
  • Case Study: Civic engagement in urban housing policy

Module 8: Building and Sustaining Network Projects

  • Designing long-term network interventions
  • Engaging stakeholders across sectors
  • Monitoring network changes over time
  • Embedding SNA into organizational workflows
  • Capacity building and institutionalization
  • Case Study: Sustaining a cross-sector anti-poverty coalition

Training Methodology

  • Interactive lectures and real-time demos
  • Hands-on exercises with open-source tools
  • Group projects and peer collaboration
  • Expert-led case study walkthroughs
  • Assessment through mini-projects and reflection
  • Mentorship and post-course support

Register as a group from 3 participants for a Discount

Send us an email: [email protected] or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.

Course Information

Duration: 5 days
Location: Accra
USD: $1100KSh 90000

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