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Tracking most-used sources on Twitter for Arab Spring coverage

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Citizen journalism and social media have become major sources for the news, especially after the Arab uprisings of early 2011.

From Al Jazeera's program Stream and NPR's Andy Carvin to the Guardian's "Three Pigs" advertisement, news organizations recognize that journalism is just one part of a broader ecosystem of online conversation...

Audience analytics and source verification only paint part of the picture. While upcoming technologies will help newsrooms understand their readers and better use citizen sources, we remain blind to the way the news is used in turn by citizen sources to gain credibility and spread ideas. That's a loss for two reasons. Firstly, it opens newsrooms up to embarrassing forms of media manipulation. Most importantly, we're analytically blind to one of bloggers' and citizen journalists' greatest incentives: attention.

Re-imagining media representation

For my MIT Media Lab master's thesis, I'm trying to re-imagine how we think about media representation in online media ecosystems. I developed a visualization of media representation in Global Voices, which has been reporting on citizen media far longer than most news organizations...

Media representation in Global Voices: Egypt and Libya

My starting questions were simple: Whose voices (from Twitter) were most cited in Global Voices' coverage of the Arab uprisings, and how diverse were those voices? Was Global Voices just amplifying the ideas of a few people, or were they including a broad range of perspectives?

Global Voices was generous enough to share its entire English archive going back to 2004, and I built a data visualization tool for exploring those questions across time and sections:

The simple demo shows the power of tracking source diversity, source popularity, and the breadth of topics that a single source is quoted on. I'm excited about taking the project further, to look at:

  • Comparing sources used by different media outlets
  • Auto-following sources quoted by a publication, as a way for journalists to find experts, and for audiences to connect with voices mentioned in the media
  • Tracking and detecting media manipulators
  • Developing metrics for source diversity, and developing tools to help journalists find the right variety of sources
  • Journalist and news bias detection, through source analysis
  • Comparing the effectiveness of closed source databases like the Public Insight Network and Help a Reporter Out to open ecosystems like Twitter, Facebook, and online comments. Do source databases genuinely broaden the conversation, or are they just a faster pipeline for PR machines?
  • Tracking the role of media exposure on the popularity and readership of social media accounts

If you're interested in continuing the conversation, try out my Global Voices Twitter Citation Viewer (tutorial here), or email me at natematiasATgmail.com.

Image: CC-licensed on Flickr.

To read the full article, click here.

This article first appeared on the site of IJNet’s partner, PBS MediaShift's Idea Lab, a group weblog by innovators who are reinventing community news for the Digital Age. Each author won a grant in the Knight News Challenge to help fund a startup idea or to blog on a topic related to reshaping community news. The complete article is translated in full into IJNet’s six other languages with permission.

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