Visualizing Big Data: Social Network Analysis by Michael Lieberman #CASRO #MRX


Live blogging from the CASRO Digital conference in San Antonio, Texas. Any errors or bad jokes are my own.CasroDigital

Visualizing Big Data: Social Network Analysis”
New open source programs, such as NodeXL, a free Excel back-end module, are making the visualization and analysis of social network data more accessible and robust. This presentation will provide the fundamentals of Social Network Analysis (SNA), provide sample Twitter and Facebook maps, and show how they may be used for enhancing marketing research on the socialmediaosphere.

Michael Lieberman, Founder, Multivariate Solutions

  • SNA – social network analysis – patterns of connection when people follow, reply, and mention one another on internet communications like twitter
  • Jacob Moreno did a chart of football in the 1930s. NSA uses it today to map terrorist networks. Embedded image permalink
  • Why SNA? How to improve the network, uncover patterns in relationships, follow the paths of information, for quant or branding research
  • Excel, open source system to map twitter, facebook, flickr, youtube, voson, wiki data. It’s easy but there is a learning curve. NODxl
  • Clients don’t want to learn about regression, they want to learn what to DO
  • Need to know – how many people can this person reach, how likely is this person to be the most direct route between two people in the network, how fast, how well connected to other well connected people
  • Degree, Betweenness, Closeness, Eigenvector (influencer)
  • Everyone really cares about who the influencers are but we learned yesterday that influencers are the worst responders
  • Brand maps have many islands – lots of people who don’t talk to anyone else. And then clusters of people who focus on specific topics. Auto companies need to know who the unconnected people are to pull them into their own groups.
  •  Broadcast map is good for celebrities like Lady Gaga.
  • Twitter is unstable, try one every day for 30 days. Hyperlinks are far more stable over time.
  • See some examples here  

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  1. […] Big Data: Social Network Analysis Take-aways from #CASRO – LoveStats Blog […]

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