Social Network Analysis: Your Questions Answered

USAID’s Sustainable WASH Systems Learning Partnership (SWS) conducts a baseline Social Network Analysis in Kabarole, Uganda, 2018. Photo Credit: Duncan McNicholl

This is the concluding blog in a series on Social Network Analysis in WASH. The other blogs in the series explore practices to help water maintenance service providers make strategic decisions to improve WASH systems and ways to apply SNA best practices in WASH work.

USAID’s Sustainable WASH Systems Learning Partnership (SWS) hosted an online training in April 2021, on how to design and implement social network analysis (SNA) in the water, sanitation, and hygiene (WASH) sector. SNA is an invaluable instrument that visually displays relationships among network stakeholders, allowing them to more effectively work with and leverage their relationships for change. 

Rich Fromer from LINC is a leader in SNA and an SWS partner. During the training, he presented case studies from the program along with WASH experts, Cliff Nyaga from Fundifix in Kenya and Joel Mukanga from Whave Solutions in Uganda. They shared how their organizations have participated in and benefited from several LINC-led SNAs over the past three years. Below are five questions to help WASH partners understand the potential of SNA.



When conducting a network analysis, how do you ensure that respondents provide candid answers?


Respondents often provide answers based on how they genuinely feel and behave, but sometimes they offer answers they think the interviewer wants to hear. To avoid this, it is best to conduct the SNA in tandem with qualitative interviews to more fully interpret the network’s nuances and entirety of its dynamics.

Additionally, best practice is to ensure those collecting and interpreting SNA data have had enumerator training and receive guidance throughout the study process. That way, they can probe deeper if they are under the impression they are not getting the most truthful answers. 


Can SNA help to answer who should be well-connected? Or does it just answer who is not connected?


Network analysis itself can only provide you with findings and observations about how the network is structured. For example, it can provide insight into which actors are most central, how well coordinated the network is on the whole, and network gaps. However, SNA cannot present why the network structure is the way it is. Network analyses provide a great starting point for direct conversations with the stakeholders about the overall network quality because they know the context and relationships, and can provide insight into what an improved network may look like. 

To make sure that we include the people who might not be connected, we typically recommend that the researchers use multiple sources to determine the respondents to include in the network/analysis, including from other network members. In most networks, this is very achievable and we are not limited by the researchers' perspectives. There are also methods to data collection (like a snowball approach that expands the network to new respondents based on the previous respondents' referrals) to further minimize that risk.

We can also compare SNA observations to our initial hypotheses and/or our theory of change to see if the actors we would expect to be central are actually well-connected or not.


What ethical considerations should implementers be aware of prior to conducting SNA?


Network analysis has some limitations on anonymizing data. It is critical that prior to any data collection, all actors participating in the survey are fully aware of how and where the data will be used, and who will see any portion of survey data and results. Prior to collecting data, obtain permission to share information and responses and ethically manage the data itself. 

While actor names can be anonymized, other personal characteristics may make it easy for others to infer the actor. At the same time, findings may be less relevant or profound if anonymized.


Relationships are dynamic and networks shift across time. Does this give SNA a short half-life of usefulness? 


In general, network changes and relationship dynamics take time to evolve. This means that the most important knowledge gained through SNA is relevant for long enough to apply it. When you begin a new initiative, you are entering an existing network structure. That is why it is important to conduct an SNA during program design to understand stakeholder roles and influencers, and what knowledge and skills they provide. Understanding the network ecosystem can be a great advantage to any new program. These dynamics take time to shift, making SNA information relevant for a while. 

As networks shift, SNA becomes useful to conduct at regular intervals (e.g., every 12 or 24 months). This allows enough time for networks to evolve, and for the SNA to detect observable and insightful trends. 

For example, SWS conducted a midterm and endline SNA with the WASH network in South Ari, Ethiopia where partners are working to advance maintenance systems of water supply infrastructure. A comparison of these two studies indicated that over time, direct coordination within the WASH network had increased by as much as 135 percent in some cases.

Data regarding network trends can also be gleaned from other documents and sources, such as email or meeting minutes.


How do we use network analysis to bring all stakeholders and entities together to create a harmonized framework and avoid duplicating efforts?


Network analysis is meant to augment and support concrete social initiatives. You can engage stakeholders in all stages of SNA. Having stakeholders collaboratively design the SNA goals and objectives is key because they are in a better position to then take the study results and collectively plan for and apply the findings to the initiative at hand. There are online platforms, like kumu and pando that allow groups to conduct SNA independently, though subscriptions may be required.

Network analysis has its limitations, as discussed, and conducting a full analysis requires time and training. Yet, the rich network relationship information gleaned from SNAs has been shown to improve the WASH sector, offering clear evidence to strategically plan the design, implementation, and monitoring and evaluation phases of programs. 

Learn More
  • Listen to online training on how SWS partners used SNA during key program stages in Ethiopia, Kenya, Uganda, and Cambodia.
  • Read about a case in Debre Birhan, Ethiopia, where repeated analyses prompted the creation of a learning alliance to improve the town’s sanitation services that demonstrated significant influence on both town dialogue and budgeting decisions. 
  • Explore practices to help water maintenance service providers make strategic decisions to improve WASH systems and ways to apply SNA best practices in WASH work. 


By Erin Fiorini, Communications Associate for Sustainable WASH Systems Learning Partnership (SWS)