Research ArticleSOCIAL SCIENCES

Using Internet search data to examine the relationship between anti-Muslim and pro-ISIS sentiment in U.S. counties

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Science Advances  06 Jun 2018:
Vol. 4, no. 6, eaao5948
DOI: 10.1126/sciadv.aao5948
  • Fig. 1 Standardized coefficients from two-stage least-squares regression model predicting pro-ISIS Internet search rate normalized by overall search activity in 3099 U.S. counties, 2014–2016.

    Red circles describe standardized coefficients, and blue bars describe 90 and 95% confidence intervals (adjusted R2 = 0.43). The coefficient for the normalized anti-Muslim search rate is the strongest and only statistically significant predictor of pro-ISIS search volume.

  • Fig. 2 Interaction between anti-Muslim Internet search rate and ethnic homogeneity index on pro-ISIS Internet search rate in 3099 U.S. counties, 2014–2016.

    Red line describes standardized coefficients from multivariate linear model, and blue band describes 95% confidence interval. Histogram on the x axis describes the frequency of counties by ethnic homogeneity. The coefficient for anti-Muslim Internet search rate increases as the ethnic homogeneity index grows in size, suggesting stronger associations between anti-Muslim Internet searches and pro-ISIS Internet searches in counties with high ethnic homogeneity compared to those with low ethnic homogeneity.

  • Fig. 3 Interaction between anti-Muslim Internet search rate and poverty rate on pro-ISIS Internet search rate in 3099 U.S. counties, 2014–2016.

    Red line describes standardized coefficients from multivariate linear model, and blue band describes 95% confidence interval. Histogram on the x axis describes the frequency of counties by poverty rate. The coefficient for anti-Muslim Internet search rate increases as the poverty rate increases suggesting stronger associations between anti-Muslim Internet searches and pro-ISIS Internet searches in counties with high poverty rates compared to those with low poverty rates.

  • Fig. 4 Correlation matrix for all variables from multivariate two-stage least-squares model.

    Blue circles describe variables that have a positive correlation with each other, and red circles describe those that have negative correlations with each other. The size of the circles corresponds to the magnitude of the bivariate correlation.

  • Table 1 Descriptive statistics.
    IndicatorNMeanSDMinimumMaximum
    Pro-ISIS search rate31462.417.650180
    Normalized pro-ISIS search rate309919.66264.91−698.864964.53
    Anti-Muslim search rate31467.1112.28070
    Normalized anti-Muslim search rate309987.26819.83−1397.729929.06
    Population size314698,139.08312,766.6009,818,605
    Percent Muslim31430.0020.0100.29
    Unemployment rate31460.090.0300.3
    Percent foreign-born31460.040.0601
    Percent male31460.50.030.431
    Population per square mile3146259.081723.36069,467.50
    High school completion rate31460.820.0800.99
    Nonviolent crime rate31430.040.0300.6
    Ethnic homogeneity index31460.730.1900.99
    Percent adolescents31430.140.0200.24
    Welfare spending per capita31410.080.1502.59
    Percent unmarried males31430.410.080.10.76
    Poverty rate31460.160.0600.62

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/4/6/eaao5948/DC1

    fig. S1. Standardized coefficients from two-stage least-squares regression model predicting pro-ISIS search rate normalized by Internet penetration in 2921 U.S. counties, 2014–2016.

    fig. S2. Standardized coefficients from two-stage least-squares regression model predicting pro-ISIS Internet search rate normalized for overall search activity in 3146 U.S. counties, 2014–2016.

    table S1. Results of Google Correlate searches to examine algorithmic confounding.

    table S2. Individuals who were indicted for terrorist activity or completed an attack by state.

    table S3. Individuals who were indicted for terrorist activity or completed an attack by year.

  • Supplementary Materials

    This PDF file includes:

    • fig. S1. Standardized coefficients from two-stage least-squares regression model predicting pro-ISIS search rate normalized by Internet penetration in 2921 U.S. counties, 2014–2016.
    • fig. S2. Standardized coefficients from two-stage least-squares regression model predicting pro-ISIS Internet search rate normalized for overall search activity in 3146 U.S. counties, 2014–2016.
    • table S1. Results of Google Correlate searches to examine algorithmic confounding.
    • table S2. Individuals who were indicted for terrorist activity or completed an attack by state.
    • table S3. Individuals who were indicted for terrorist activity or completed an attack by year.

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