Really interesting analysis of twitter use in US politics. I’m sure this can be replicated for other contexts.
From kohenari:

Is Twitter Politically Polarized?

Yes, according to a new paper by M. D. Conover, J. Ratkiewicz, M. Francisco, B. Goncalves, A. Flammini, and F. Menczer …. But there still is some interesting interaction between Twitter users from different political perspectives.
The authors use an algorithm to identify 250,000 Twitter messages (from a database of 355 million tweets gathered over a six week period) with politically relevant hashtags, coming from about 45,000 users. What’s interesting is that they identify quite different dynamics as operating within two different communication networks. One network is composed of retweets – where one user simply retweets another’s message. Here, they find that this network is densely clustered, so that left-leaning people retweet messages from other leftwingers, and right-leaning people retweet messages from other rightwingers. However, there is a second network, composed of ‘mentions’ – where one Twitter user mentions another’s user name in order to communicate with him or her. This network is far more heterogenous, as can be seen from the figure below (the retweet network is linkmapped on the left, the mention network on the right). This can be interpreted with a positive or negative normative slant, depending.
The authors lean towards the latter interpretation. They also generously provide their dataset (located at http://cnets.indiana.edu/groups/nan/truthy ) for others interested in exploring the “role of technologically-mediated political inter- action in deliberative democracy.”

Really interesting analysis of twitter use in US politics. I’m sure this can be replicated for other contexts.

From kohenari:

Is Twitter Politically Polarized?

Yes, according to a new paper by M. D. Conover, J. Ratkiewicz, M. Francisco, B. Goncalves, A. Flammini, and F. Menczer …. But there still is some interesting interaction between Twitter users from different political perspectives.

The authors use an algorithm to identify 250,000 Twitter messages (from a database of 355 million tweets gathered over a six week period) with politically relevant hashtags, coming from about 45,000 users. What’s interesting is that they identify quite different dynamics as operating within two different communication networks. One network is composed of retweets – where one user simply retweets another’s message. Here, they find that this network is densely clustered, so that left-leaning people retweet messages from other leftwingers, and right-leaning people retweet messages from other rightwingers. However, there is a second network, composed of ‘mentions’ – where one Twitter user mentions another’s user name in order to communicate with him or her. This network is far more heterogenous, as can be seen from the figure below (the retweet network is linkmapped on the left, the mention network on the right). This can be interpreted with a positive or negative normative slant, depending.

The authors lean towards the latter interpretation. They also generously provide their dataset (located at http://cnets.indiana.edu/groups/nan/truthy ) for others interested in exploring the “role of technologically-mediated political inter- action in deliberative democracy.”

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