Digital Activism Research: Learning a Lot About a Little

Kony tweets: a gorgeous N of 1 (source: Gilad Lotan)

We now know a tremendous amount about the Kony 2012 campaign and excellent analysis keeps rolling in: on the Ushahidi blog, Patrick Meier has posted a variety of responses from Ugandans and Ethan Zuckerman has posted a gorgeous visualization fromGilad Lotan of the first 5000 Kony tweets (see left). At a panel at SXSW yesterday, I learned that Invisible Children plans to release their own data on the campaign.

As a digital activism researcher this makes me happy, because we need more empirical qualitative and quantitative analysis of digital activism, and most of the analysis I have read is of this type: nuanced, data-driven, analytically sophisticated. At the same time, it is just one case. We are learning a lot about a little.

This reminds me of 2009, when there was so much attention paid to the use of digital technology in the Iranian post-election protests. Excellent research was conducted by the Web Ecology Project, The Center for International Media Assistance, and The United States Institute of Peace. This happened again in 2011 when in-depth survey data on citizen media use during the Egyptian Revolution was collected by The Engine Room and analyzed by Zeynep Tufekci. The problem with intense but uneven data collection is that there is little basis for comparison. In academic terms, we are left with an N of 1.

I am not criticizing the intense analysis of the Kony case, or any of the other cases. I am pushing for an awareness that knowing a lot about a few cases has limited value because there is a great danger of making baseless extrapolations about how the lessons learned in Iran, Egypt, or the Kony case apply to other digital activism cases. What does our knowledge about media choices in Egypt tell us about media choices in Syria? What will Kony tell use about the next viral video? We don’t know.

The Global Digital Activism Data Set is collecting and comparatively analyzing digital activism cases, but our data is mostly qualitative and narrative. We don’t have network analyses like Gilad’s. For every digital activism case for which we have detailed information, there are thousands for which we know little or nothing. Even as we laud the empirical analysis of individual digital activism cases, we must work for the funding, tools, and academic interest that will allow the Gilad Lotans of the world to conduct their analyses not only on single digital activism cases, but on hundreds.

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