Demographic Differentials in Facebook Usage Around the World

We use data from the Facebook Advertisement Platform to study patterns of demographic disparities in usage of Facebook across countries. We address three main questions: (1) How does Facebook usage differ by age and by gender around the world? (2) How does the size of friendship networks vary by age and by gender? (3) What are the demographic characteristics of specific subgroups of Facebook users? We find that in countries in North America and northern Europe, patterns of Facebook usage differ little between older people and younger adults. In Asian countries, which have high levels of gender inequality, differences in Facebook adoption by gender disappear at older ages, possibly as a result of selectivity. We also observe that across countries, women tend to have larger networks of close friends than men, and that female users who are living away from their hometown are more likely to engage in Facebook use than their male counterparts, regardless of their region and age group. Our findings contextualize recent research on gender gaps in online usage, and offer new insights into some of the nuances of demographic differentials in the adoption and the use of digital technologies.Comment: Accepted at a poster at ICWSM 2019. Please cite the ICWSM versio

Close Social Networks Among Older Adults:The Online and Offline Perspectives

Qualitative studies have found that the use of Information and Communication Technologies is related to an enhanced quality of life for older adults, as these technologies might act as a medium to access social capital regardless of geographical distance. In order to quantitatively study the association between older people’s characteristics and the likelihood of having a network of close friends offline and online, we use data from the Survey of Health, Ageing and Retirement in Europe and data from Facebook. Using a novel approach to analyze aggregated and anonymous Facebook data within a regression framework, we show that the associations between having close friends and age, sex, and being a parent are the same offline and online. Migrants who use internet are less likely to have close friends offline, but migrants who are Facebook users are more likely to have close friends online, suggesting that digital relationships may compensate for the potential lack of offline close friendships among older migrants

Studying Social Interactions Using Digital Trace Data: the Cases of Older Adults, Migrants, and Family Ties

This thesis contributes to the growing field of Computational Social Science by using data from Facebook and Twitter to study: the differential usage of Facebook around the world; older people’s close friendships; immigrants’ language acquisition; and European regional family ties. The first study was a descriptive comparative analysis of the use of Facebook by older and young people worldwide. The second study showed how, in the European Union, the likelihood of having close friends differs between older people who use the internet and Facebook compared to older people who live offline. The third study used data from Twitter to analyze how civic integration and citizenship requirements in the EU-15 are associated with immigrants’ median times to start tweeting in the language of the host society. The final study focused on the European regional family ties distinction, hypothesizing on whether European North-South differences in family dynamics are reflected in Twitter users’ conversations as well

Migration Policies and Immigrants’ Language Acquisition in EU-15: Evidence from Twitter

In response to the increasingly complex and heterogeneous immigrant communities settling in Europe, European countries have adopted various civic integration measures. Measures aiming to facilitate language acquisition are considered crucial for integration and cooperation between immigrants and natives. Simultaneously, the rapid expansion of social media usage is believed to change the factors affecting immigrants’ language acquisition. However, only a few previous studies have analyzed whether this is the case. This article uses a novel longitudinal data source derived from Twitter to (1) analyze differences in the pace of immigrants’ language acquisition depending on the migration policies of destination countries and (2) study how the relative sizes of the migrant groups in destination countries, and the linguistic and geographical distances between origin and destination countries, are associated with language acquisition. Results show that immigrants who live in countries with strict language acquisition requirements for immigrants and conservative citizenship policies have the highest median times until language acquisition. Based on Twitter data, we also find that language acquisition is associated with classic explanatory variables, such as the size of the immigrant group in the destination country and the linguistic and geographical distance between origin and destination country similar to the previous studies.Policy Analysi

Digital and computational demography

Digital and computational demography explores demography in relation to the digital revolution - the rapid technological improvements in digitized information storage, computational power and the spread of the internet and mobile technologies since the turn of the new millennium. We cover three ways in which the digital revolution touches upon demography. First, we discuss how digital technologies, through their impacts on daily lives and in shifting how individuals access information, communicate and access services, have implications for demographic outcomes linked to health and mortality, fertility and family, and migration. Second, we discuss how the digital revolution has created a wide range of new data sources such as digital trace and geospatial data that can be repurposed for demographic research, and enabled respondent recruitment across the world via the internet and social media. Third, we discuss how improvements in computational power have facilitated the use of computational methods such as microsimulation and agent-based modelling as well as machine learning techniques for demographic applications. We conclude by discussing future opportunities and challenges for digital demography