论文标题

Facebook广告是衡量城乡鸿沟的人口工具

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

论文作者

Rama, Daniele, Mejova, Yelena, Tizzoni, Michele, Kalimeri, Kyriaki, Weber, Ingmar

论文摘要

在全球朝着城市化方面的发展中,确保留在农村地区的人们在发展和政策考虑方面并没有落伍,这是全球政府的优先事项。但是,跟踪有关这种稀疏,地理分散的人群的重要统计数据越来越具有挑战性,导致缺乏可靠的,最新的数据。在这项研究中,我们研究了Facebook广告平台的有用性,该平台提供了超过20亿用户的数字“人口普查”,以衡量潜在的农村城市不平等现象。我们专注于意大利,这个国家约有30%的人口居住在农村地区。首先,我们表明,Facebook会产生的人口统计数据跨时间不稳定,并且对人口稀少的市政当局的覆盖不完全。为了克服这种限制,我们提出了一种估算Facebook广告受众的替代方法,该方法几乎将农村城市的覆盖范围从19%降至55%,并进行可行的细粒度亚人群分析。使用官方的国家人口普查数据,我们评估了我们的方法,并在教育成果和收入方面确认已知的重大城乡鸿沟。将分析扩展到特定于Facebook的用户“兴趣”和行为,我们为鸿沟提供了进一步的见解,例如,发现农村地区对赌博表现出更高的兴趣。值得注意的是,我们发现农村地区收入的最预测特征与城市中心的收入不同,这表明研究人员在检查农村福祉时需要考虑更广泛的属性。这项研究的结果说明了改善现有工具和方法的必要性,以包括数字人群研究中代表性不足的人群 - 未能这样做可能会导致误导性的观察,结论,最重要的是政策。

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.

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