Analyzing gender inequality through large-scale Facebook advertising data

Online social media are information resources that can have a transformative power in society. While the Web was envisioned as an equalizing force that allows everyone to access information, the digital divide prevents large amounts of people from being present online. Online social media in particular are prone to gender inequality, an important issue given the link between social media use and employment. Understanding gender inequality in social media is a challenging task due to the necessity of data sources that can provide large-scale measurements across multiple countries. Here we show how the Facebook Gender Divide (FGD), a metric based on aggregated statistics of more than 1.4 Billion users in 217 countries, explains various aspects of worldwide gender inequality. Our analysis shows that the FGD encodes gender equality indices in education, health, and economic opportunity. We find gender differences in network externalities that suggest that using social media has an added value for women. Furthermore, we find that low values of the FGD are associated with increases in economic gender equality. Our results suggest that online social networks, while suffering evident gender imbalance, may lower the barriers that women have to access informational resources and help to narrow the economic gender gap

Personality filters for online news interest and engagement

Our many online routines leave behind trails of data about our identities, habits, preferences and connections. These data serve as filters when we seek out information, yielding relevant results and content of interest. However, commercial and political parties can use the same data to personalize persuasive messages, and some even use psychological profiles to target individuals. With this revelation come concerns that news can be framed to appeal to individual personalities. This study investigates the relationship between personality and news engagement among predominantly young Norwegian adults across different news angles. It addresses the Big Five personality traits as well as rational and experiential information-processing styles. The results provide support for our hypothesis on the relation between neuroticism and lowered news engagement, although the effect sizes are small. When exploring iso- lated news stories, we find greater differentiation among the participants, suggesting that individuals’ news interest really does start at the headline.Personality filters for online news interest and engagementpublishedVersio

Can Patience Account for Subnational Differences in Student Achievement?

Decisions to invest in human capital depend on people’s time preferences. We show that differences in patience are closely related to substantial subnational differences in educational achievement, leading to new perspectives on longstanding within-country disparities. We use social-media data – Facebook interests – to construct novel regional measures of patience within Italy and the United States. Patience is strongly positively associated with student achievement in both countries, accounting for two-thirds of the achievement variation across Italian regions and one-third across U.S. states. Results also hold for six other countries with more limited regional achievement data

Facebook Ads as a Demographic Tool to Measure the Urban-Rural Divide

In the global move toward urbanization, making sure the people remaining in rural areas are not left behind in terms of development and policy considerations is a priority for governments worldwide. However, it is increasingly challenging to track important statistics concerning this sparse, geographically dispersed population, resulting in a lack of reliable, up-to-date data. In this study, we examine the usefulness of the Facebook Advertising platform, which offers a digital "census" of over two billions of its users, in measuring potential rural-urban inequalities. We focus on Italy, a country where about 30% of the population lives in rural areas. First, we show that the population statistics that Facebook produces suffer from instability across time and incomplete coverage of sparsely populated municipalities. To overcome such limitation, we propose an alternative methodology for estimating Facebook Ads audiences that nearly triples the coverage of the rural municipalities from 19% to 55% and makes feasible fine-grained sub-population analysis. Using official national census data, we evaluate our approach and confirm known significant urban-rural divides in terms of educational attainment and income. Extending the analysis to Facebook-specific user "interests" and behaviors, we provide further insights on the divide, for instance, finding that rural areas show a higher interest in gambling. Notably, we find that the most predictive features of income in rural areas differ from those for urban centres, suggesting researchers need to consider a broader range of attributes when examining rural wellbeing. The findings of this study illustrate the necessity of improving existing tools and methodologies to include under-represented populations in digital demographic studies -- the failure to do so could result in misleading observations, conclusions, and most importantly, policies.Comment: To be published in the Proceedings of The Web Conference 2020 (WWW '20

A utilização de dados pessoais sensíveis na formação do perfil comportamental de pessoas naturais e o potencial dano aos seus titulares

Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Faculdade de Direito, 2019.A Nova Lei Geral de Proteção de Dados, LGPD, configura-se como importante instrumento normativo que servirá como principal vetor na regulação do tratamento de dados pessoais no Brasil, especialmente os dados pessoais sensíveis. Desse modo, o presente trabalho tem como objetivo analisar a utilização desses dados pessoais sensíveis na formação de perfis de comportamento e de modelos classificatórios e preditivos, que geram danos aos titulares dessas informações pessoais e criam ou fomentam cenários discriminatórios, seja no âmbito laboral, em discussões políticas ou até mesmo no que diz respeito aos dados de saúde coletados. Também serão abordadas ferramentas, como o estímulo das boas práticas de governança, capazes de mitigar tais cenários desfavoráveis aos usuários. A fim de subsidiar tal análise, foram utilizadas as revisões bibliográfica e legislativa do tema, que tem como ponto central a Lei n. 13.709/2018 e, subsidiariamente, o General Data Protection Regulation. Por fim, a análise do objeto de estudo foi feita com o intuito de despertar e desenvolver alguns pontos importantes que fomentam inúmeras discussões as quais a LGPD deverá enfrentar, principalmente, a partir de agosto de 2020.The New General Data Protection Act, LGPD, is an important normative instrument that serves as the main control vector for the processing of personal data in Brazil, especially the identified personal data. Thus, the present work aims to analyze the use of this sensitive personal data in the formation of behavioral profiles and classifying and predictive models, which cause damage to the holders of this personal information and create or foster discriminatory scenarios, either at work, in political discussions or even regarding the health data collected. Tools should also be addressed, such as encouraging good governance practices that can mitigate them for users. In order to support this analysis, the bibliographic and legislative reviews of the theme were used, which has as its central point Law 13,709/2018 and, in the alternative, the General Data Protection Regulation. Finally, the analysis of the object of study was made in order to awaken and develop some important points that foment countless discussions that LGPD will face, mainly, from August 2020