In late June at a conference in
Boston, Michael Wu, a scientist with Lithium Technology demonstrated the power
of social network analysis by asking the audience at his presentation to tweet
notes on his speech live (Carr, 2012).
The result of the live tweeting would serve as evidence for the content
of his speech (Carr, 2012). The live
tweeting would show the connections between the network of audience members and
the retweets of those tweets would demonstrate the best regarded of those in
the audience (2012).
Wu’s employed by Lithium to as a data analytics leader for the Lithium Technology, which provides social community software and used this live tweeting tool to demonstrate the power of understanding social network analysis, and understanding that being highly networked does not necessarily mean that that individual holds power over their connections. (At about 27:00 of this video, you can see the results of his experiment: http://www.informationweek.com/thebrainyard/e2-boston-2012)
Wu’s employed by Lithium to as a data analytics leader for the Lithium Technology, which provides social community software and used this live tweeting tool to demonstrate the power of understanding social network analysis, and understanding that being highly networked does not necessarily mean that that individual holds power over their connections. (At about 27:00 of this video, you can see the results of his experiment: http://www.informationweek.com/thebrainyard/e2-boston-2012)
I thought this article was an
interesting application of some of our readings. In particular, Cross, Borgatti and Parker’s
(2002) illustrative examples of social network analysis as a management tool, enabling
mangers to visualize the ways information is actually shared within a network.
References
Cross, R., Borgatti, S., and Parker, A. (2002) Making
invisible work visible: using social network analysis to support strategic collaboration,
California Management Review, 44,
25-46
Carr, D. F. (2012). Social network analysis live onstage. Information Week. Retrieved from http://www.informationweek.com/news/240002060
Cynthia, you say that the network of tweets were able to show the 'best regarded' audience members. Because we learned about network methods this week through the Hanneman and Riddle (2005) textbook, can you take any guesses on how the program calculated 'best regarded'? Are these people central in the network? Are they bridges? Liaisons? Have the most contacts? Also, could you explain more about the idea that more connections does not necessarily equal more power?
ReplyDeleteI second Dr. Pade's comments and in consideration of them ask, I wonder what chaos theory has to say about Twitter and if it tweaks the meaning of social butterfly? :)
DeleteDr. Pade, he interprets "best regarded" as most often retweeted, not the person who tweeted the most often. So reading and sharing was interpreted as more valuable than simply tweeting and being read; you may have a lot of connections, but if those connections are not acting, is there value? Your question about bridges and liaisons in the case of Twitter is interesting, is Twitter about networks and ties? Because I follow someone on Twitter, but never retweet or respond, am I really in that network? This could become a really deep philosophical conversation.
ReplyDelete