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Of Autopsies and Analytics

by Carol Rozwell  |  March 13, 2013  |  4 Comments

Recently, I read an interesting article from MIT Tech Review which diagnosed why the social network Friendster failed – An Autopsy of a Dead Social Network.

The research done by David Garcia and colleagues at the Swiss Federal Institute of Technology in Zurich concluded that networks with a significant percentage of participants who had two friends were highly vulnerable to collapse. On some level, this sounds intuitively right. In my research into why social projects fail (Social Projects Require Project Managers to Think Differently), we identified a critical mass of participants as a critical success factor. It’s nice to see some research which backs up the point and explains the observation.

Coincidentally, I also had the opportunity to speak with Remi Kirche from describes itself as a social network of blogs: a blogging solution which includes native communication tools and social features. What I found interesting about our discussion is the way uses predictive analytics to give value back to its members. They find that people who have friends on the network get more value from the communities they join and they participate more. When someone comes into the network, they can quickly develop friends. Predictive analytics lets can see the communities and understand the interactions. This allows them to make recommendations to advertisers about which communities are a potentially valuable market for them.

There are a couple of points worth considering for those people tasked with rolling out social software solutions inside their organizations. Based on our research, we know that adoption of social tools is still a struggle. Simply giving employees social tools and waiting ‘to see what happens’ doesn’t work.

If we buy the premise that gaining active participation in a network is essential for its survival, then we need to help the participants figure out who might be worth ‘meeting.’ It’s quite similar to the real world counterpart of creating ways to ‘break the ice’ at meetings, parties and other face-to-face events. The sooner we get people engaged with like-minded people, the more likely they are to stay engaged and view the event positively.

This seems like an increasingly useful way to employ analytics: use the knowledge of affinity to quickly create connections. Give the network of workers with an affinity (aka work to get done) a place to meet and a reason for meeting. In addition to setting up the meet, use analytics to monitor the health of the interactions looking at measures such as frequency, duration and increase in connections.

I’m looking forward to continuing my research into this exciting topic.

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Category: change-management  collaboration  community  social-media  social-networks  social-software  

Tags: change-management  collaboration  collaboration-dynamics  collective  communities-of-practice  metrics  organizational-change  social-analytics  social-network-analysis  social-networking  social-networks  social-software  

Carol Rozwell
VP Distinguished Analyst
11 years at Gartner
21 years IT industry

Carol Rozwell is a vice president and distinguished analyst on Gartner's Digital Workplace team. Read Full Bio

Thoughts on Of Autopsies and Analytics

  1. Carol, very interesting post.

    The fact that analytics can help “monitor the health of the interactions looking at (…) frequency and duration” is a crucial point. Many people see a social network as something “frozen” in time – but it’s alive! It evolves over time, gains or loses connections, etc.

    But it can be hard for some technologies to monitor that dynamically on a large scale, i.e on very big networks.

    I would love to hear some comments ad real-life examples on this.

  2. Carol Rozwell says:

    Thanks for your comment, Julien. In previous Gartner research, I listed five case studies of social network analysis. Rob Cross also has two excellent books on SNA that have many examples.

    That being said, I am continually surprised by how difficult it is to get people to talk about their use of SNA. It’s so evident it can provide useful insight on how the organization really is working, or where it is not.

    We’ll keep looking for cool examples and posting them when we can.

  3. Excellent post. Yes, Rob Cross work is very good. Check out his new relationship with Activate Networks founded by Nicholas Chritsakis and James Fowler. Network analysis is being used on massive networks at Yahoo (most recently Duncan Watts, now at Microsoft). I recommend his very readable book “Everything is Obvious After the Fact” which describes social network dynamics, influence patterns, and provides insight into possible uses in large organizations which may adopt Facebook like applications. Lada Adamic is another social network analysis academic who is currently at Facebook on leave from Univ. of Michigan. FB has their own very useful Data Science group worth following. Lad also runs a terrific free online course on SNA via Coursera.

  4. Carol Rozwell says:

    Victoria, thank you for the excellent suggestions.

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