March 13, 2018

Social network analysis: What can mapping your network do for you?

Before jumping into our topic today, we think some introductions are in order… We’re a passionate group of knowledge mobilizers – practitioners and consultants who help others translate research knowledge into action. We meet regularly to think and talk about knowledge mobilization and evaluation. It’s all about learning from –  and collaborating with – one another.  We each have unique backgrounds and skill sets that provide perspectives that challenge our thinking. We’ve come together because we all value one thing in particular – motivating change through knowledge mobilization. Apart from collaborating together on various projects, we have also teamed up to start a series of blogs to start opening our conversations up to you!

Today, our caffeinated discussions focused on the value of social media analytics and social network analysis. With new analytics for Twitter, and an ever growing array of social media metrics, there seem to be more and more opportunities for looking at social networks. We thought it might be interesting to see how these tools could inform more complex social network analyses to describe and inform knowledge mobilization and knowledge networks.

So… what can mapping your network do for you?

Well first off, let’s consider what a social network is. A ‘social network’ is a collection of social interactions and personal relationships an individual has established. So you’re probably thinking, ‘yea, like my Facebook or Twitter account’ – and you’re right. Social networking sites like Facebook and Twitter are perfect examples of online social networks. Whether online, or in person, we all establish social networks in life – both personally and professionally. Analyzing these networks, through Social Network Analysis (SNA) allow us to better understand how individuals are connected, and most importantly, how information flows – this is critical for improving communication and mobilizing knowledge.

SNA is about measuring, mapping, and visualizing relationships and information flows between individuals in a group or organization. It’s a set of methods based on network theory, and uses mathematics to model these networks. So SNA looks at all actors within a network and asks ‘where are they located?’ and ‘how are they linked?’. The unit of analysis therefore is focused not on the individual itself, but on the larger network of individuals and the linkages that connect them.

There are two key pieces to any SNA map, (1) nodes, and (2) ties. Nodes represent individual actors within the network (i.e. the dots in the attached figure (Tenerife, 2015)). Ties connect the nodes (i.e. the lines connected the dots in the figure below); these ties show relationships between each actor in the network, which allow us to visualize how information flows through the network. You’ll also often hear about ‘hubs’ – these refer to individuals within the network that (i) have a large number of direct connections to other individuals in the network, and (ii) are located in between other important actors who are not connected. In other words, ‘hubs’ are crucial to the flow of information because they can gather and disseminate information from numerous sources AND they provide indirect connections between other influential individuals in the network.

By analyzing social networks in this way we can learn many things, such as: who can reach the largest audience, who is most likely to bring fresh ideas to the table, who is connected to the most influential individuals, and who mediates important relationships. We can also find out where the network is weakest. If two parts of a network rely on only one or two nodes then the network is rather frail, because the flow information is dependant upon those one or two nodes for information. Therefore, SNA provides a useful approach to evaluating social networks and can be invaluable for understanding how to improve knowledge mobilization.

There’s some specific terminology with SNA, which allow us to answer questions like:

Who has the most direct connections? – Degree Centrality

Who is the link between two or more important groups? – Betweenness Centrality

Who has the shortest path to all others in the network? – Closeness Centrality

SNA Options for Knowledge Mobilization

We’ve briefly described three approaches to using SNA in knowledge mobilization below, with resources required ranging from yarn to specialized software:

On the spot/facilitated.

An in-person activity where you use yarn to map connections among key actors, organizations, and stakeholder groups for a given issue. Record those connections on a paper or electronic network map. Use yarn and pushpins on cork boards if space or mobility is limited.

  • Pros
    • interactive, in-person exercise that builds shared understanding of connections and networks
    • participatory approach for diverse audiences
  • Cons
    • may be based on incomplete knowledge of connections (if using participants perceptions of 3rd party relationships)
    • can be confusing if instructions are unclear (yarn tangle)
  • Tips
    • you’ll need at least 90 minutes (at a minimum) – more time makes a better map
    • use photos and a note taker to record the network map

Survey-based.

Send out online or paper-based survey questions about type, quality, and/or quantity of relationships and connections among key actors, organizations, and stakeholder groups for a given issue.

  • Pros
    • stakeholders can report on their own connections
    • captures links between people who are physically distant (can’t be brought together in the same room) or who are too busy for a live session
    • survey can target influencers and be easily tailored to local contexts
  • Cons
    • low response rate to survey may bias results
    • can be time consuming to transfer survey results to a social network map
  • Tips
    • connect the survey to specific research questions to increase motivation to complete the survey – why are you collecting these data? how will you use the information?
    • Compare actual and perceived connections between actors and organizations to identify barriers to knowledge exchange.

Social media-based analysis.

Use software like NodeXL to analyze connections through Twitter or other social media.

  • Pros:
    • comprehensive (within the social network). Identify connections and patterns using a large data set
    • can examine networks for knowledge exchange on very specific issues and dates
  • Cons:
    • can’t capture connections and conversations outside of online social networks
    • many available tools require specialized skills/expertise
  • Tips
    • Need to target searches or results can be overwhelming.
    • For Mac users, try NodeXL in a free Amazon EC2 PC: bit.ly/d52TCj – Add Office & remote desktop to it. (thanks to @marc_smith for the tip)

Conclusions

SNA is a process for looking at  at the population/group/organization/network to understand how information flows. Isn’t that what most knowledge mobilizers are after too? We think there are serious opportunities here to begin visualizing and assessing change in knowledge mobilization networks, and SNA is a strong methodology to get us there. In the world of social media, apps, and constant technological innovation, our communication approaches, and ability to connect, are changing quicker than ever before. SNA goes beyond the specific communication medium, and seeks to understand how messages are, or are not, getting to those that need it.

Coming soon…

Our next set of blogs are going to start looking at how we practice what we’ve just preached. We’re going to get into online applications of SNA and look at some results. So stay tuned! Don’t forget to follow us as we will be updating more routinely from now on.

Have a question, comments, or general feedback? Feel free to get in touch with us on Twitter, or through our websites

Resources

References

Tenerife, D. 2015. Social Network Analysis – Meso Level. Available online: https://en.wikipedia.org/wiki/Social_network. Accessed on June 17, 2015.

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