Lithium Technology scientist will conduct live experiment in social network analysis and collaborative work in Enterprise 2.0 keynote.
10 Social Acquisitions Signify Bigger Trends
(click image for larger view and for slideshow)
When Michael Wu walks onstage for his Enterprise 2.0 keynote on Tuesday, fire up your Twitter account, because he is going to need your help.
As chief scientist at Lithium Technology, Wu leads data analytics for the social community software firm. As part of his Enterprise 2.0 Boston keynote presentation, he will be conducting a live experiment in social network analysis at the same time he explains the concept. The plan is for the audience to take notes and post them as a rapid-fire series of Twitter posts, retweeting the best posts from other audience members as they go. Wu will then use that conversation as the source for an impromptu analysis.
"I want to show that collectively, as an audience, we can produce a really complete set of notes on what I talk about," Wu said. In addition to identifying the points in his speech that the audience finds most interesting, the analysis should also show something about the connections between the audience members and who some of the most influential members are.
This is not intended as a software demonstration. Although Lithium has its own social media monitoring technology, Wu said he uses many tools in his work and also writes his own software, sometimes in Pig Latin (the scripting language for Pig, a big data analytics tool).
In addition to keynoting, Wu will give a more in-depth presentation as part of a Monday afternoon workshop on social analytics and metrics with Rawn Shah, a business transformation consultant at IBM. Shah will present a general framework for understanding social media analytics, while Wu will present case studies based on the experience of Lithium customers. At last year's Boston event, Wu joined me on a panel discussion on big data and social analytics, and he also joined Shah in a previous edition of the analytics workshop at Enterprise 2.0 Santa Clara.
Wu said one of his goals in Boston is to help attendees understand the many dimensions of social media analytics. "If you're analyzing the social network, there are many ways a person can be important. I may look at the most connected person, and I think that's important. But that's a fallacy in the social media world--just because you're popular doesn't mean you're important. I might want to look at other things, like are they a critical gatekeeper. Are they the closest path to all the critical communications in a network?"
By the time Wu's keynote ends, we should know a little more about the answers to those questions in the context of the Enterprise 2.0 audience. As for me, I'm going to practice typing faster to make sure I at least show up somewhere on his radar.
Follow David F. Carr on Twitter @davidfcarr. The BrainYard is @thebyard and facebook.com/thebyard
The Enterprise 2.0 Conference brings together industry thought leaders to explore the latest innovations in enterprise social software, analytics, and big data tools and technologies. Learn how your business can harness these tools to improve internal business processes and create operational efficiencies. It happens in Boston, June 18-21. Register today!
The Agile ArchiveWhen it comes to managing data, don’t look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyIT’s tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.
InformationWeek Tech Digest, Nov. 10, 2014Just 30% of respondents to our new survey say their companies are very or extremely effective at identifying critical data and analyzing it to make decisions, down from 42% in 2013. What gives?