30 mars 2013
NodeXL: Learning from Visualizations of Social Media Networks
This is a guest post by Lisa Rhody, who works for the Roy Rosenzweig Center for History and New Media at George Mason University as the project manager for WebWise 2013.
In last week’s post about social network analysis, I introduced NodeXL and its potential use for understanding online social networks. In this post, I want to focus on what we can learn from conference Twitter backchannel conversations, and how we can use software like NodeXL to improve the way we use social media to build computer-mediated scholarly networks.
During this year’s annual meeting of the Modern Language Association, I worked with Marc Smith, co-founder of the Social Media Research Foundation and chief social scientist for Connected Action, to upload several sample datasets that mapped Twitter networks at the conference. On Friday, January 4, 2013, Marc uploaded a social media network graph of tweets that included the hashtag from this year’s MLA convention to the NodeXL Gallery. Read more...
In last week’s post about social network analysis, I introduced NodeXL and its potential use for understanding online social networks. In this post, I want to focus on what we can learn from conference Twitter backchannel conversations, and how we can use software like NodeXL to improve the way we use social media to build computer-mediated scholarly networks.
During this year’s annual meeting of the Modern Language Association, I worked with Marc Smith, co-founder of the Social Media Research Foundation and chief social scientist for Connected Action, to upload several sample datasets that mapped Twitter networks at the conference. On Friday, January 4, 2013, Marc uploaded a social media network graph of tweets that included the hashtag from this year’s MLA convention to the NodeXL Gallery. Read more...
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