Pardon me while I become a social scientific nerd for a moment. But there’s nothing simple about an online community. Sure, the internet facilitates connections between people who are interested in similar things. We think of them like little virtual villages of like-minded people, which are easy to visit and eavesdrop on, especially if they’re talking about issues that pertain to the service or product your company offers.
If only that were so. But the truth is conversations in those online villages are not like genteel tea parties where everyone has an equal say and participates equally. They are highly organized – not dissimilar to a complex ecosystem in the Galapagos Islands. And if you don’t understand how they work – who are essential to the connections that occur and who are less important – you’re not maximizing their market research potential for your company.
I have always felt that companies were missing out on important insights that could be gleaned from what I call a “deep dive” into the social intricacies of online communities. Five years ago, when social media was still just a one-dimensional “thing” for many companies, I made it my mission to find programs that would look at the value of the social media networks. I wanted to go deeper than reporting on volume of tweets or followers. I wanted to know more about the connections that are being made; the conversations people are having; and most important, who those people are.
The programs most social media marketers use weren’t enough. So I sought out the experts in the business.
One of the programs I came across was created by Marc Smith, a sociologist specializing in the social organization of online communities and computer mediated interaction. He founded the Community Technologies Group at Microsoft Research in Redmond, Washington and led the development of social media reporting and analysis tools for Telligent Systems. Smith leads the Connected Action consulting group and currently lives and works in Silicon Valley, California. He is a co-founder of the Social Media Research Foundation which is dedicated to Open Tools, Open Data, and Open Scholarship related to social media.
I have had several long conversations with Marc. One of the first things we discussed was the value of Program NODXL. It allows us to know who has added what content and with what authority to a specific online social media project.
The bottom line is that you want to gather insightful sentiment and identify “mayors of communities” or “influencers” which is the latest buzzword in Social Media.
To properly understand – and leverage – these online networks and their participants for the purposes of
research, marketing or sales, we evaluate the location of people (or nodes) in the network.
Like I said, it’s all quite scientific. And the diagram below – The Kite Network developed by David Krackhardt, a leading researcher in social networks – looks a bit like a molecular structure in a science lab. (Or the labyrinthine dynamics of schoolyard cliques!)
But rest assured. It is easy to understand. And the value is tremendous. These measures give us enormous insight into the various roles and groupings in a network. Below we can walk through how these social networks work together as described by Vladis Krebs. Popular Science has described Krebs as a “leading expert” and a “pioneer” of network analysis.
Two nodes (or people) are connected if they regularly talk to each other or interact in some way. Andre regularly interacts with Carol, but not with Ike. Therefore Andre and Carol are connected, but there is no link drawn between Andre and Ike.
This network effectively shows the distinction between the three most popular individual centrality measures: Degree Centrality, Betweenness Centrality, and Closeness Centrality.
Social network researchers measure network activity for a node (person) by using the concept of degrees — the number of direct connections a node (person) has. In the Kite Network above, Diane has the most direct connections in the network, making hers the most active node in the network. She is a ‘connector’ or ‘hub’ in this network. Common wisdom in personal networks is “the more connections, the better.” But this is not always so.
What really matters is where those connections lead to – and how they connect to the otherwise unconnected! Here Diane has connections only to others in her immediate cluster — her clique. She connects only those who are already connected to each other.
While Diane has many direct ties, Heather has few direct connections: fewer than the average in the network. Yet, in many ways, she has one of the best locations in the network: she is between two important constituencies. She plays a ‘broker’ role in the network. The good news is that she plays a powerful role in the network; the bad news is that she is a single point of failure. Without her, Ike and Jane would be cut off from information and knowledge in Diane’s cluster. A node with high betweenness has great influence over what flows — and does not — in the network. Heather may control the outcomes in a network. That is why I say, “As in real estate, the golden rule of networks is: Location, Location, Location.”
Fernando and Garth have fewer connections than Diane, yet the pattern of their direct and indirect ties allow them to access all the nodes in the network more quickly than anyone else. They have the shortest paths to all others. They are close to everyone else. They are in an excellent position to monitor the information flow in the network. They have the best visibility into what is happening in the network.
Individual network centralities provide insight into the individual’s location in the network. The relationship between the centralities of all nodes can reveal much about the overall network structure.
A very centralized network is dominated by one or a few very central nodes. If these nodes are removed or damaged, the network quickly fragments into unconnected sub-networks.
A highly central node (Person) or “influencer” can become a single point of failure. A network centralized around a well-connected hub can fail abruptly if that hub is disabled or removed.
Hubs are nodes with high degree and betweenness centrality.
A less centralized network has no single points of failure. It is resilient in the face of many intentional attacks or random failures. Many nodes or links can fail while allowing the remaining nodes to still reach each other over other network paths. Networks of low centralization fail gracefully.
Not all network paths are created equal. More and more research shows that the shorter paths in the network are more important. Noah Friedkin, Ron Burt and other researchers have shown that networks have horizons over which we cannot see nor influence. They propose that the key paths in networks are 1 and 2 steps and on rare occasions, 3 steps. The “small world” in which we live is not one of “six degrees of separation” but of direct and indirect connections – 3 steps away. Therefore, it is important to know who is in your network neighborhood, who are you aware of and who can you reach.
In the network above, who is the only person that can reach everyone else in two steps or less?
Network metrics are often measured using geodesics — or shortest paths. They make the (erroneous) assumption that all information/influence flows along the network’s shortest paths only. But networks operate via direct and indirect, shortest and near-shortest paths.
We often hear interesting things from various sources in the network. Different interpretations arrive via different paths.
It is important to be on many efficient paths in networks that reach out to various parts of the extended network.
Nodes (people) that connect their group to others usually end up with high network metrics. Boundary spanners such as Fernando, Garth, and Heather are more central in the overall network than their immediate neighbors whose connections are only local – within their immediate cluster. You can be a boundary spanner via your bridging connections to other clusters or via your concurrent membership in over-lapping groups.
Boundary spanners are well-positioned to be innovators, since they have access to ideas and information flowing in other clusters. They are in a position to combine different ideas and knowledge, found in various places, into new products and services.
Boundary Spanners are the “influencers” that are often overlooked in the simple social network analysis programs.
Most people would view the nodes on the periphery of a network as not being very important. In fact, Ike and Jane receive very low centrality scores for this network. Since individuals’ networks overlap, peripheral nodes are connected to networks that are not currently mapped. Ike and Jane may be contractors or vendors that have their own network outside of the company — making them very important resources for fresh information not available inside the company.
When creating network maps and metrics for your business or even your own work, Krebs explains that the maps and metrics are mirrors not report cards. They’re only as good as the questions you ask or the goals for creating them. If you work with a consultant to look at your maps and projets together you will make sense of what the maps/metrics reflect about your organization. The consultant will bring external expertise and context, while you as the business owner or particular internal department will provide internal context about the organization and its goals.