Building Networks - Understanding Who Is Involved

On Nov. 3 and 4 I participated in a two day event called City/Cité: A Transatlantic Exchange, that was an exploration of inequality, race and the state of Urban Democracy in the United States, France and beyond. Speakers were from both sides of the Atlantic. As the event unfolded attendees were encouraged to use Twitter to share what was happening in one small Chicago space to others in Chicago and throughout the world who are concerned with the same issues.

A couple of months ago I learned of a network analysis mapping tool called NodeXL, which enables mapping of Twitter and Facebook hashtags, to create a visualization showing participation over a defined time-frame. I posted a tutorial on the MappingforJustice blog so that I could learn more about this, and so others could do their own learning.

This morning I asked Mark Smith, from NodeXL to create a map using "#citycite_Chicago OR #urbandemocracy", the two main hashtags for the event. That map is shown below and at this link.

Because of the small number of Tweeters, there are no dense clusters on this map. However, you can see how some people were the center of larger groups, who retweeted or commented on their own Tweets. Lines from one node to another, and from one cluster to another, show connectivity between different people. Since this is a small group, and I was active, you can see @tutormentorteam in the upper right cluster on the map.

Below is another NodeXL map, showing Twitter activity during the Independent Sector conference, which was held in Florida, attracting a huge crowd of participants. Some sessions were live streamed (and archived), meaning people who could not make it to the conference could still participate. Independent Sector(@indsector) promoted the conference via Twitter and encouraged active Tweeting the day of the event, using "#ISEmbarks OR #embarkstream" hashtags. The map of Twitter activity is shown below. The link is here.

This graph "represents a network of 1,451 Twitter users whose recent tweets contained "#ISEmbarks OR #embarkstream", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Wednesday, 28 October 2015 at 21:00 UTC."

This is a much larger group of users than who participated in the City/Cité event. The map shows a few large clusters connected to each other, and many smaller groups.

I'm part of the big cluster at the lower left part of this graph, toward the right side of the main cluster. This graphic illustrates how you can enlarge the graphic to view different sections, and shows my @tutormentorteam node.

I'm just learning to use this, and don't have a lot of time to focus on the tool, or to create maps to analyze, and create map stories, about individual events. Thus, I encourage you to read the tutorial I posted to learn ways to use NodeXL and similar network analysis tools.

One way that I feel is really important is for event and movement organizers to build an understanding of how many people are connecting to each other as a result of the event and its on-line conversations. While the issues of race and poverty and inequality are really important, the City/Cité event this week did not draw nearly the number of Twitter participants as did the Independent Sector's focus on philanthropy.

However, these are connected issues. In my own opinion, there should be some evidence of people who focus on race, poverty and inequality being involved in both of these events.

Another way anyone can use these graphs is to look at who the main influencers are. These might be people you'd want to follow on Twitter, and build a relationship with. You can enlarge the graph, and move your mouse over each node, or each cluster, to identify more participants, and find more people you'd want to connect with.

In yesterday's discussion of race, poverty and inequality one speaker ended his comments saying "The real challenge is making more people care". I agree. However, part of that challenge is attracting people to conversations that focus on these issues, and then mapping participation so you know who is there, and who is missing.

The graphic below visualizes this challenge. How do a few of us multiply, over and over, to the point where we have a critical mass of people who are giving time, talent and dollars to reduce inequity, reduce poverty, improve opportunity, reduce racism and violence, etc.? How do we engage people who don't live with these issues every day, who live in areas of wealth, privileged and affluence, and deal with their own problems every day, giving very little consistent attention to the problems of others. Once we get someone's attention, how do we connect them with the vast amounts of information they could use to support growing involvement? How do we keep them involved, and expanding their knowledge and commitment, for decades?

Social network analysis maps, Geographic Maps, and concept maps could begin to show who is involved, and provide paths that connect people with each other, and with ideas.

I've been trying to do this since 2010. This graphic is from a set of blog articles showing participation in 2008 and 2009 Tutor/Mentor Conferences. In this article you can see work done by students who were part of a 2015 Information Visualization MOOC hosted by Indiana University. Each of these were short term projects. This type of work requires on-going involvement, mapping lots of events, not just the ones I've hosted.

Every day someone in Chicago, or in other parts of the world, is hosting an event focused on issues that are important to me and others. Many of these are beginning to have an on-line component. If organizers of face-to-face events think of network-building as a goal, and focus on strategies that keep people connected to each other after an event ends, more might begin to add online activities into their strategies, and use hashtags, network analysis and mapping tools, and newer technologies to know the network, nudge the network, and build the network so it reaches a scale that can solve some of the complex problems that bring us together in the first place.

Read Network Analysis articles on Scribed. Here, Here and Here