Abstract Geographic variation in digital inequality manifests as a result of a range of demographic, attitudinal, behavioural and locational factors. To better understand this multidimensional geography, our paper develops a new geodemographic classification for the spatial extent of Great Britain. In this model, we integrate a range of new small area measures that are drawn from multiple new forms of data including consumer purchasing data, survey and open data sources. Our analytical approach innovatively provides an integration of machine learning into a small-area estimation technique to obtain Lower Super Output Area / Data Zone estimates of Internet use, alongside a range of online engagement and consumption measures. Following the collation of a range of input measures, we implemented a more standard geodemographic framework that utilises the unsupervised clustering algorithm k-means to produce a map of the multidimensional characteristics of digital inequality for Great Britain; creating the Internet User Classification (IUC). Our outputs provide a new and nuanced understanding of the contemporary salient characteristics of digital inequality in Great Britain, which we evaluate both internally and externally within the context of preparations for the 2021 UK Census of the Population, exploring the geodemographic patterns of Census test response rates and the prevalence to complete the survey online. Our innovative work illustrates the strength of a geodemographic approach in mapping spatial patterns of digital inequality, and through the presented application concerning Census response rates and characteristics we demonstrate how the IUC can be operationalised within such settings for local intervention or benchmarking.

中文翻译：

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绘制英国数字不平等的地理人口统计图：机器学习与小区域估计的整合

摘要 数字不平等的地理差异表现为一系列人口、态度、行为和位置因素的结果。为了更好地理解这种多维地理，我们的论文为英国的空间范围开发了一种新的地理人口学分类。在这个模型中，我们整合了一系列新的小范围衡量指标，这些衡量指标来自多种新形式的数据，包括消费者购买数据、调查和开放数据源。我们的分析方法创新地将机器学习集成到小区域估计技术中，以获得互联网使用的下超级输出区域/数据区估计，以及一系列在线参与和消费措施。在整理了一系列输入措施之后，我们实施了一个更标准的地理人口学框架，该框架利用无监督聚类算法 k-means 来生成英国数字不平等的多维特征图；创建互联网用户分类 (IUC)。我们的产出提供了对英国数字不平等当代显着特征的全新而细致入微的理解，我们在准备 2021 年英国人口普查的背景下进行内部和外部评估，探索人口普查测试响应率的地理人口模式以及在线完成调查的患病率。我们的创新工作说明了地理人口学方法在绘制数字不平等的空间模式方面的优势，