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Digital Resistance in Repressive Regimes
The document discusses the impact of digital resistance on the public sphere, focusing on examples of protests facilitated by information and communication technologies (ICT) from various countries. It examines whether ICT serves as a statistically significant predictor of protest events through data-driven methods and regression analysis. Preliminary findings suggest a negative correlation between internet access and protest occurrences, while mobile access does not show significant effects.
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Digital Resistance in Repressive Regimes
- 1. Is Digital ResistanceReshaping the Public Sphere? Patrick P. Meier The Fletcher School at Tufts & Berkman Center, Harvard University
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- 4. Philippines ‘01 -“Coup de Text” DigiActive
- 5. Philippines ‘01 -“Coup de Text” Spain ‘04 - “The Night of SMS” DigiActive
- 6. Philippines ‘01 -“Coup de Text” Pakistan ‘07 - “Flash Protests” DigiActive Spain ‘04 - “The Night of SMS”
- 7. Philippines ‘01 -“Coup de Text” Tibet - “Media Blackout?” Spain ‘04 - “The Night of SMS” Pakistan ‘07 - “Flash Protests”
- 8. Tibet - “MediaBlackout?” Morocco ‘08 - “Exposing Abuse” Spain ‘04 - “The Night of SMS” Pakistan ‘07 - “Flash Protests”
- 9. Tibet - “MediaBlackout?” Morocco ‘08 - “Exposing Abuse” Egypt - “Exposing Torture” Pakistan ‘07 - “Flash Protests”
- 10. Tibet - “MediaBlackout?” Morocco ‘08 - “Exposing Abuse” China - “Live-Twittered Arrest” Egypt - “Exposing Torture”
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- 12. ICT a statisticallysignificant predictor of protests events?
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- 16. Data-driven Eyck 2001Stodden and Meier 2008
- 17. Data-driven Eyck 2001Stodden and Meier 2008
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- 20. Parameters Protests ICTsControls
- 21. Parameters Protests ICTsControls Time period 1990-2007 country-year
- 22. Parameters Protests ICTsControls Time period 1990-2007 country-year 22 regimes
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- 26. Graphs Protests InternetMobiles
- 27. Summary Stats N= 396
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- 30. Regressions y i,t = i + 1 Int i,t + 2 Mob i,t + 3 Land i,t + 4 Autoc i,t + 5 Unemp i,t + 6 GDP i,t + i,t
- 31. Regressions Observed vs Projected
- 32. Observed vs Projected F i = y obs,i - y model,i
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- 34. Results* *preliminary, subjectto change
- 35. Results* Internet -0.12(0.03) 99% sig level
- 36. Results* Internet -0.12(0.03) 99% sig level Mobiles -0.06 (0.06) not significant
- 37. Results* Internet -0.12(0.03) 99% sig level Mobiles -0.06 (0.06) not significant Other variables not significant
- 38. Results* Rsq =0.613 Rsq = 0.155
- 39. 6. Conclusion &Next
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- 41. Thoughts Why? Othermethods?
- 42. Thoughts Why? Othermethods? Field research!
- 43. Thank You [email_address]www. iRevolution .wordpress.com <- blog Twitter @patrickmeier
Editor's Notes
- #2 First chapter of dissertation Numerous qualitative case studies and even more anecdotes on digital media in repressive regimes What does this all add up to? Can we start measuring the aggregate impact of digital activism on repressive rule? Does digital resistance, that is, digital activism applied to strategic nonviolent action, threatening repressive regimes? Is digital resistance reshaping the public sphere? How can analyze quantitatively the qualitative, anecdotal impact of digital resistance, or lack thereof?