This document summarizes a study that analyzed the relationship between internet use and participation in protests across 40 countries. The study used data from the World Value Survey and multilevel logistic regression modeling. The results found that internet use significantly increases the probability of protest participation by 52% on average. However, the effect varied widely by country, from a slight positive effect to a strong positive effect in some developing countries. The study aims to further analyze how country-level factors like internet penetration and human rights influence the relationship between internet use and protest participation.

1. The Internet as a Factor of Participation in
Protests: Cross Country Analysis
Kirkizh Eleonora, Olessia Koltsova
Higher School of Economics (SPb)

2. Structure
• Theory
• Hypothesis
• Data and Method
• Results
• Conclusions
• Further research

3. Theory
Theory of Information Society
The direct link between politics, media and the crisis of political legitimacy
in a global perspective.
The development of interactive, horizontal networks of communication has
induced the rise of a new form of communication, mass self-communication,
over the Internet and wireless communication networks. (Castells, 2007)
Discussion
Protesters in Northern African and Middle East countries have been using
social networks for coordination and information exchange. (Breuer, 2012)
Using Facebook or Twitter, citizens created groups where they posted news,
calls, announcements and other items concerning protests. (Gaffney, 2009,
Allagui, 2011)
Protests in Chile, Iran, Belgium, Spain and the Arab countries.
(Lotan, 2011, González-Bailón, 2013)

4. Hypothesis
H1: Probability of protest participation of citizens is more if
they use the Internet as a information resource.
(Howard, 2010)
H2: Probability of protest participation is higher if a citizen
(unemployed, middle income, has political interest, well
educated) uses the Internet as a information resource.
(Gaffney, 2009, Wolfsfeld, 2012, Korotaev, 2013)

5. Data and Method
World Value Survey, wave 6 (2011-2013)
Countries: 40
Individuals: over 42,000
Variables:
• Dependent: protest participation
• Independent: employment status, age, confidence: the government,
income, information recourse: Internet, friends, post materialist index
(4-item), age, education, religiosity, political view.
• Group level variable: country
Method: multilevel logistic regression

6. Coefficient St. Error
internet (yes) 0.421*** (0.036)
friends (yes) 0.314*** (0.044)
education
high
–0.273***
(0.046)
low
–0.620***
(0.048)
politics (yes) 0.739*** (0.032)
post materialist
mixed
0.275***
(0.036)
post
0.694***
(0.050)
religious (yes) –0.187*** (0.040)
age
mid
–0.301***
(0.036)
young
–0.440***
(0.048)
employment (yes) –0.104* (0.057)
views
mixed
–0.564***
(0.036)
right
–0.561***
(0.038)
Observations 44,146
Pseudo R-squared 0.140
Regression results
Model 1
Note: *p<0.1; **p<0.05; ***p<0.01

7. Model 1 Model 1* Internet
friends (yes) 0.314***
(0.044)
–0.076
(0.088)
education (high) –0.273***
(0.046)
–0.205*
(0.094)
politics (yes) 0.739***
(0.032)
0.114
(0.061)
post materialist (mixed) 0.275***
(0.036)
0.224
(0.087)
religious (yes) –0.187***
(0.040)
0.056
(0.075)
age (mid) –0.301***
(0.036)
0.054
(0.058)
employment (yes) –0.104*
(0.057)
–0.317**
(0.111)
views (mixed) –0.564***
(0.036)
–0.571***
(0.036)
Observations 44,146
Pseudo R-squared 0.140
Regression results
Model 1
Model 1* with
interactive effects
Note: *p<0.1; **p<0.05; ***p<0.01

10. Conclusions
Individual level
• The average regression coefficient for the Internet use across 40 countries
equals 0.42. The probability of whether a citizen, reading news on the
Internet, joins a protest is 52% higher than if he/she does not. (H1)
• Different interactive effects. Mostly the Internet is not a significant factor.
(H2)
Group level
• The effect of the Internet is positive in most countries. Only in three states –
Japan, Kazakhstan and Peru – the effect is negative.
• In other countries usage of the Internet turns to be a significant positive
predictor. However, coefficients of the effects among them vary vastly:
from 0.1 to 0.8.
• Five groups of the countries with the lowest effect of the Internet to the
highest effect. The highest coefficients (0.7–0.8) were observed in the
following countries: Chile, Colombia, Ghana, Tunisia, Libya, Yemen,
and Pakistan. (Kalathil, 2003)

11. Further research
• Analysis with group level variables (the Internet
penetration, GDP, Human Rights Risk Index,
Corruption Rate etc.)

12. Thank you for your attention
Questions?