68 research outputs found

    Demographic Differentials in Facebook Usage Around the World

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    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

    Leveraging digital and computational demography for policy insights

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    Situated at the intersection of the computational and demographic sciences, digital and computational demography explores how new digital data streams and computational methods advance the understanding of population dynamics, along with the impacts of digital technologies on population outcomes, e.g. linked to health, fertility and migration. Encompassing the data, methodological and social impacts of digital technologies, we outline key opportunities provided by digital and computational demography for generating policy insights. Within methodological opportunities, individual-level simulation approaches, such as microsimulation and agent-based modelling, infused with different data, provide tools to create empirically informed synthetic populations that can serve as virtual laboratories to test the impact of different social policies (e.g. fertility policies, support for the elderly or bereaved people). Individual-level simulation approaches allow also to assess policy-relevant questions about the impacts of demographic changes linked to ageing, climate change and migration. Within data opportunities, digital trace data provide a system for early warning with detailed spatial and temporal granularity, which are useful to monitor demographic quantities in real time or for understanding societal responses to demographic change. The demographic perspective highlights the importance of understanding population heterogeneity in the use and impacts of different types of digital technologies, which is crucial towards building more inclusive digital spaces

    Professional Gender Gaps Across US Cities

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    Gender imbalances in work environments have been a long-standing concern. Identifying the existence of such imbalances is key to designing policies to help overcome them. In this work, we study gender trends in employment across various dimensions in the United States. This is done by analyzing anonymous, aggregate statistics that were extracted from LinkedIn's advertising platform. The data contain the number of male and female LinkedIn users with respect to (i) location, (ii) age, (iii) industry and (iv) certain skills. We studied which of these categories correlate the most with high relative male or female presence on LinkedIn. In addition to examining the summary statistics of the LinkedIn data, we model the gender balance as a function of the different employee features using linear regression. Our results suggest that the gender gap varies across all feature types, but the differences are most profound among industries and skills. A high correlation between gender ratios of people in our LinkedIn data set and data provided by the US Bureau of Labor Statistics serves as external validation for our results.Comment: Accepted at a poster at ICWSM 2018. Please cite the ICWSM versio

    Fertility and its Meaning: Evidence from Search Behavior

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    Fertility choices are linked to the different preferences and constraints of individuals and couples, and vary importantly by socio-economic status, as well by cultural and institutional context. The meaning of childbearing and child-rearing, therefore, differs between individuals and across groups. In this paper, we combine data from Google Correlate and Google Trends for the U.S. with ground truth data from the American Community Survey to derive new insights into fertility and its meaning. First, we show that Google Correlate can be used to illustrate socio-economic differences on the circumstances around pregnancy and birth: e.g., searches for "flying while pregnant" are linked to high income fertility, and "paternity test" are linked to non-marital fertility. Second, we combine several search queries to build predictive models of regional variation in fertility, explaining about 75% of the variance. Third, we explore if aggregated web search data can also be used to model fertility trends.Comment: This is a preprint of a short paper accepted at ICWSM'17. Please cite that version instea

    Covid-19: A Tsunami That Amplifies Existing Trends in Demographic Research

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    The author argues that the Covid-19 pandemic highlighted the increasing importance of data innovation, and the role of digital connections for social relationships and as determinants of health and inequalities

    Rock, Rap, or Reggaeton?: Assessing Mexican Immigrants' Cultural Assimilation Using Facebook Data

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    The degree to which Mexican immigrants in the U.S. are assimilating culturally has been widely debated. To examine this question, we focus on musical taste, a key symbolic resource that signals the social positions of individuals. We adapt an assimilation metric from earlier work to analyze self-reported musical interests among immigrants in Facebook. We use the relative levels of interest in musical genres, where a similarity to the host population in musical preferences is treated as evidence of cultural assimilation. Contrary to skeptics of Mexican assimilation, we find significant cultural convergence even among first-generation immigrants, which problematizes their use as assimilative "benchmarks" in the literature. Further, 2nd generation Mexican Americans show high cultural convergence vis-\`a-vis both Anglos and African-Americans, with the exception of those who speak Spanish. Rather than conforming to a single assimilation path, our findings reveal how Mexican immigrants defy simple unilinear theoretical expectations and illuminate their uniquely heterogeneous character.Comment: WebConf 201

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

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    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
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