Although women’s participation in tertiary education and the labour force has expanded over the past decades, women continue to be underrepresented in technical and managerial occupations. We analyse if gender inequalities also manifest themselves in online populations of professionals by leveraging audience estimates from LinkedIn’s advertisement platform to explore gender gaps among LinkedIn users across countries, ages, industries and seniorities. We further validate LinkedIn gender gaps against ground truth professional gender gap indicators derived from the International Labour Organization’s (ILO) Statistical Database, and examine the feasibility and biases of predicting global professional gender gap indicators using gender gaps computed from LinkedIn’s online population. We find that women are significantly underrepresented relative to men on LinkedIn in countries in Africa, the Middle East and South Asia, among older individuals, in Science, Technology, Engineering and Mathematics (STEM) fields and higher-level managerial positions. Furthermore, a simple, aggregate indicator of the female-to-male ratio of LinkedIn users, which we term the LinkedIn Gender Gap Index (GGI), shows strong positive correlations with ILO ground truth professional gender gaps. A parsimonious regression model using the LinkedIn GGI to predict ILO professional gender gaps enables us to expand country coverage of different ILO indicators, albeit with better performance for general professional gender gaps than managerial gender gaps. Nevertheless, predictions generated using the LinkedIn population show some distinctive biases. Notably, we find that in countries where there is greater gender inequality in internet access, LinkedIn data predict greater gender equality than the ground truth, indicating an overrepresentation of high status women online in these settings. Our work contributes to a growing literature seeking to harness the ‘data revolution’ for global sustainable development by evaluating the potential of a novel data source for filling gender data gaps and monitoring key indicators linked to women’s economic empowerment.

尽管在过去几十年中妇女接受高等教育和劳动力的人数有所增加，但妇女在技术和管理职业中的代表性仍然不足。我们通过利用 LinkedIn 广告平台的受众估计来探索不同国家、年龄、行业和资历的 LinkedIn 用户之间的性别差距，分析性别不平等是否也体现在在线专业人群中。我们根据来自国际劳工组织 (ILO) 统计数据库的真实职业性别差距指标进一步验证 LinkedIn 性别差距，并检查使用从 LinkedIn 在线人口计算的性别差距预测全球职业性别差距指标的可行性和偏差。我们发现，在非洲、中东和南亚国家，在年龄较大的人中，在科学、技术、工程和数学 (STEM) 领域以及更高级别的管理职位中，女性在 LinkedIn 上的代表性明显低于男性。此外，LinkedIn 用户男女比例的一个简单的综合指标，我们称之为 LinkedIn 性别差距指数 (GGI)，显示出与 ILO 基本事实职业性别差距的强烈正相关。使用 LinkedIn GGI 预测国际劳工组织专业性别差距的简约回归模型使我们能够扩大不同国际劳工组织指标的国家覆盖范围，尽管一般专业性别差距的表现优于管理性别差距。然而，使用 LinkedIn 人群生成的预测显示出一些明显的偏见。尤其，我们发现，在互联网访问中存在更大性别不平等的国家/地区，LinkedIn 数据预测的性别平等程度高于基本事实，表明在这些环境中在线高地位女性的比例过高。我们的工作有助于通过评估新数据源填补性别数据差距和监测与妇女经济赋权相关的关键指标的潜力，利用“数据革命”促进全球可持续发展的越来越多的文献。