Posts tagged content analysis

This is an impressive analysis of something seemingly simple: Twitter in academia. More of this kind of analysis of “technology in the classroom” should be done, rather than speculative/intuitive guesswork.
From kohenari:

Somewhat related to yesterday’s post on the challenges associated with making significant use of Twitter in the classroom, here’s an interesting graphic on academic use of Twitter.
Click the graphic to enlarge.
HT: Kim Yi Dionne.

This is an impressive analysis of something seemingly simple: Twitter in academia. More of this kind of analysis of “technology in the classroom” should be done, rather than speculative/intuitive guesswork.

From kohenari:

Somewhat related to yesterday’s post on the challenges associated with making significant use of Twitter in the classroom, here’s an interesting graphic on academic use of Twitter.

Click the graphic to enlarge.

HT: Kim Yi Dionne.

This is a great, simple example of how to do some rudimentary content analysis. I’ll have to use it next time I teach research methods.

From shortformblog:

Does Time water down its story coverage in the U.S.? That’s a question which has been floating around the interwebs since yesterday, when the internet hivemind figured out that Time ran a soft feature in this week’s U.S. edition, while the rest of the world got a much more important story about Egypt. (Fellow Tumblr Jessica Binsch did a Storify breakdown of the online reaction.) Most of us can agree Time probably blew this cover choice. However, we’d like to offer another argument here: That the magazine is merely playing to different markets, rather than blatantly dumbing down its U.S. coverage. Our latest Tumbl-zine (it’s been a while, we know) breaks down the past year in Time covers, by region and type of content. Here’s what we found.

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.”

This has a lot of potential for simple content analysis applications in undergraduate courses. Awesome! But does it also work with other (i.e. international) news sources? I hope so!
From shortformblog:

Check out that word frequency! In case you wanted to do a real-time check of the biases of CNN vs. Fox News, this spiffy little OSX app called News Mapper does the trick. Our checks so far: CNN’s obsessed with “debt,” while Fox News has the market on “Obama” cornered. Surprisingly, though, “Boehner” is about even. This is awesome. A supergenius must’ve made this.

This has a lot of potential for simple content analysis applications in undergraduate courses. Awesome! But does it also work with other (i.e. international) news sources? I hope so!

From shortformblog:

Check out that word frequency! In case you wanted to do a real-time check of the biases of CNN vs. Fox News, this spiffy little OSX app called News Mapper does the trick. Our checks so far: CNN’s obsessed with “debt,” while Fox News has the market on “Obama” cornered. Surprisingly, though, “Boehner” is about even. This is awesome. A supergenius must’ve made this.

This would be a great project to ask students to do with American (or any other country’s) newspapers & magazines.
From theatlantic:

A Primer on British Media After the ‘News of the World’ Scandal

This would be a great project to ask students to do with American (or any other country’s) newspapers & magazines.

From theatlantic:

A Primer on British Media After the ‘News of the World’ Scandal

Beyond a nice critical analysis of contemporary e-journalism, this also offers a great way to frame content analysis of online journalism (via copyeditor, dailyhuff, i.imgur.com).
I now plan to use this in my discussion of content analysis in INST381 (Research Methods for International Studies) in a few weeks. So, um, thanks!

Beyond a nice critical analysis of contemporary e-journalism, this also offers a great way to frame content analysis of online journalism (via copyeditordailyhuffi.imgur.com).

I now plan to use this in my discussion of content analysis in INST381 (Research Methods for International Studies) in a few weeks. So, um, thanks!

European TV has a similar level of coverage for the Middle East (27%) and North America (29%), while US TV networks are more concerned with the Middle East (40%) than Europe (24%). Middle Eastern coverage suggests a much stronger interest in European affairs (36%) than events occurring in North America (21%).

While US broadcasters dedicate a higher proportion of overall coverage to the Middle East than their European counterparts, broadcasters from both regions devote more than 60% of their coverage on the Middle East to violence.

I recently asked my INST381 (Research Methods for International Studies) students to do content analysis of international newspapers, and a few of them did similar projects looking at news coverage of different areas of the world. 

From a report by Media Tenor International (via publicradiointernational).