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Analyzing gender inequality through large-scale Facebook advertising data

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PNAS July 3, 2018 115 (27) 6958-6963; first published June 19, 2018; https://doi.org/10.1073/pnas.1717781115

  1. Edited by Michael Macy, Cornell University, Ithaca, NY, and accepted by Editorial Board Member Mary C. Waters May 5, 2018 (received for review October 14, 2017)

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Figures

  • Fig. 1.
    Fig. 1.

    The FGD across 217 countries. Countries are colored according their FGD from highly skewed toward males (red) and balanced (blue) to highly skewed toward females (green; not visible). Left Inset shows the scatterplot of male and female activity ratios across all countries, revealing a spread along the diagonal. Right Inset shows the histogram of FGD values in bins of width 0.2. While the mode of countries is slightly below zero, there is significant skewness toward high FGD values. An online interactive version of this figure can be found at https://dgarcia-eu.github.io/FacebookGenderDivide/Visualization.html.

  • Fig. 2.
    Fig. 2.

    Regression results of FGD as a function of gender equality. (A) Model predictions vs. rank of FGD, where rank 1 is the country with the highest FGD. The model achieves a high R2 above 0.74, explaining the majority of the variance of the FGD ranking. Some countries are labeled, from high FGD [Liberia (LR), India (IN), and Saudi Arabia (SA)] to low FGD [Finland (FI), Norway (NO), and Uruguay (UY)], as well as some outliers [Dominican Republic (DO), Austria (AT), and Sri Lanka (LK)]. (B) Coefficient estimates and 95% CIs of the terms of the regression fit (excluding intercept). Education (Edu), health (Heal), and economic gender equality (Eco) are significantly and negatively associated with the FGD, but political gender equality (Pol) is not. From the control variables, Internet penetration (IP) is negatively associated with FGD, but the rest are not. The main role of education equality in FGD can be observed in A, where dots are colored according to the rank of education gender equality, showing that countries with low FGD are ranked high on education gender equality. An online interactive version of this figure can be found in https://dgarcia-eu.github.io/FacebookGenderDivide/Visualization.html. FBP, Facebook penetration; Ineq, income inequality; Pop, total population.

  • Fig. 3.
    Fig. 3.

    Gender differences in network externalities on Facebook. Scaling of the Facebook activity ratio per gender vs. total Facebook penetration. Solid lines show fit results, and shaded areas show their 95% CIs. Both male and female activity ratios grow superlinearly with Facebook penetration (α>1), indicating positive network externalities. These network externalities are stronger for female than for male users (αF>αM).

  • Fig. 4.
    Fig. 4.

    Analysis of changes in economic gender equality and FGD. Coefficient estimates of the regression model of changes in economic gender equality as a function of FGD and control terms (excluding intercept; Upper Left) and of the model of changes in FGD as a function of economic gender equality and control terms (excluding intercept; Lower Left). Right shows the bootstrap distributions of partial R2 of FGD2015 in the first model and of Eco2015 in the second one, with dashed vertical lines showing the median R2 values: 0.027 (Upper Right) in the first model and 0.002 (Lower Right) in the second one. The FGD explains changes in economic gender equality much better than economic gender equality explains changes in the FGD. GDP, gross domestic product.

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Analyzing gender inequality through large-scale Facebook advertising data
David Garcia, Yonas Mitike Kassa, Angel Cuevas, Manuel Cebrian, Esteban Moro, Iyad Rahwan, Ruben Cuevas
Proceedings of the National Academy of Sciences Jul 2018, 115 (27) 6958-6963; DOI: 10.1073/pnas.1717781115
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  • Social Sciences
  • Social Sciences
Proceedings of the National Academy of Sciences: 115 (27)
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