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New Map of Twitterverse Finds 6 Types of Networks

Part of a network graph of 599 Twitter users whose tweets contained "mla13" on Jan. 6, 2013.

A group of researchers has determined that most information discussed via Twitter falls into six distinct categories.

Credit: UMD Newsdesk

University of Maryland professor Ben Shneiderman, working with researchers from the Pew Research Internet Project, the Social Media Research Foundation, and the University of Georgia, has found that most of the information being discussed on Twitter falls into six distinct patterns or networks.

Their study analyzed tens of thousands of Twitter conversations over the past four years and developed a "topographical map" of these patterns based on the topic being discussed, the information and influencers driving the conversation, and the social network structures of the participants.

The six network patterns the researchers found are polarized crowds, tight crowds, brand clusters, community clusters, broadcast networks, and support networks.

"What we've done is to provide a visual map of the Twitterverse that will ultimately help others to better interpret the trends, topics, and implications of these new communication technologies," Shneiderman says.

The researchers used NodeXL, an open source program, to interpret the data. NodeXL enables researchers to examine the combination of tweets, retweets, and the social networks of Twitter users. "It could eventually have a large impact on our understanding of everything from health to community safety, from business innovation to citizen science, and from civic engagement to sustainable energy programs," Shneiderman says.

From UMD Newsdesk
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Abstracts Copyright © 2014 Information Inc., Bethesda, Maryland, USA


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