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

Weight outcomes audit for 34,271 adults referred to a primary care/commercial weight management partnership scheme

Copyright © 2011 S. Karger AG, Basel.Peer reviewedPublisher PD

Examining Connections between Gendered Dimensions of Inequality and Deforestation in Nepal

The United Nations recognizes empowering women as a key component of achieving numerous development-related goals. Qualitative studies suggest that communities where men and women have equal levels of agency over resource allocation and land tenure sometimes experience decreases in forest degradation and deforestation, all else being equal. However, these patterns are spatially heterogeneous, as are patterns of gender inequality in terms of land tenure and agency. This paper uses data from the Demographic and Health Surveys (DHS) to quantify the relationship between gender inequality and ecosystem degradation using three linear regression models, Empirical Bayesian Kriging, and mapping the intersections between gender inequality and deforestation. Results from LASSO, Ordinary Least Squares, and Stepwise regression models show that there is no linear relationship between gender inequality and deforestation. Additionally, the distributions of gender inequality as it pertains to land tenure and deforestation are highly heterogeneous over space, indicating potential sociocultural and sociodemographic factors not captured in my data. Further work should focus on identifying ways to incorporate complex gender dynamics into environmental planning at multiple levels of forest governance

Computational Sociolinguistics: A Survey

Language is a social phenomenon and variation is inherent to its social nature. Recently, there has been a surge of interest within the computational linguistics (CL) community in the social dimension of language. In this article we present a survey of the emerging field of "Computational Sociolinguistics" that reflects this increased interest. We aim to provide a comprehensive overview of CL research on sociolinguistic themes, featuring topics such as the relation between language and social identity, language use in social interaction and multilingual communication. Moreover, we demonstrate the potential for synergy between the research communities involved, by showing how the large-scale data-driven methods that are widely used in CL can complement existing sociolinguistic studies, and how sociolinguistics can inform and challenge the methods and assumptions employed in CL studies. We hope to convey the possible benefits of a closer collaboration between the two communities and conclude with a discussion of open challenges.Comment: To appear in Computational Linguistics. Accepted for publication: 18th February, 201

The Nutrition Elite: Do Only the Highest Levels of Caloric Knowledge, Obesity Knowledge, and Motivation Matter in Processing Nutrition Ad Claims and Disclosures?

This study examines the role of the highest levels of caloric knowledge, obesity consequences knowledge, and motivation to search for nutrition information in the processing of relative nutrient content claims in advertisements, such as “half the calories” or “half the fat,” for products relatively high in total calorie levels. After controlling for the impact of demographics, dietary habits, body mass index, relative ad claims and disclosures, perceived weight gain risk, and other variables, the authors find curvilinear (quadratic) effects for caloric knowledge, obesity consequences knowledge, and motivation to search for nutrition information on intent to buy an advertised, high-calorie snack bar. This suggests a strengthening of the negative relationship for intent for consumers at the highest levels of caloric knowledge, obesity consequences knowledge, and motivation (i.e., the “nutrition elite”). The authors offer public policy implications, including whether achieving such exceedingly high levels of nutrition knowledge and motivation is realistic for the general public in light of other policy alternatives, such as market-based solutions (e.g., reducing serving sizes, standardized front-of-package icons)