Who gets the most out of conferences? We attend conferences to learn and connect with others. While measuring learning remains hard, measuring the social connections formed at events is getting easier. More conference organizers may soon measure the performance of their events by measuring the connections attendees form at them.
The desktop bound era of social networking is already drawing to a close, at least about to be eclipsed by the emerging mobile network aware device. More sensors and radios on mobile devices will soon automate what is currently a manual process. As people come near people, our devices are likely to be able to connect and share data, directly and through the network, to recognize who is nearby and for how long.
Today conference organizers can create similar data by manually taking and analyzing digital photos to identify the social connections formed. The result is a complex visual web of relationships observed at the event. While some of this data should certainly be private (and there are significant issues about proper collection and use of social network data), there is great value for conference organizers and attendees if selectively shared.
Even before the next era of sensors and wearables arrives, the November 2014 Data Leadership Summit in Vancouver provided a taste of the rapidly coming future of automated social network analysis. Network data was analyzed and used to plan the event, and captured at the event itself to measure the social capital ROI resulting from the Summit. As 77 participants gathered to make connections and strengthen relationships, the conference organizers ensured pictures were taken continuously during the event to answer the question: “Who talked to whom?” These few hundred pictures provide the evidence of the many connections that formed.
We used these photos to visualize and analyze the Summit network–turning photos into network “edges” that were entered into social network analysis software–to reveal the overall shape of the connections, as well as identifying participants in key locations within the network map. For more on our photo analysis, click here. Our network maps highlight the sub-groups or “neighborhoods” of slightly more connected people that formed as a result of the Summit. Some people stand out with many diverse connections. Other people are clearly more peripheral to the group.
For groups that want to collect and share data about their interactions, there is an opportunity to gain insights into the ways some groups perform well and others do not. Network insights into the structures of successful groups may pave the way to a kind of collective biofeedback that enable groups to perform more efficiently. Network self-aware events may be more satisfying and rewarding for many of their attendees.