Understanding the gendered effects of the COVID-19 pandemic is challenging, especially due to limitations in data collection.
Big data can help fill these data gaps when traditional data is lacking or unavailable by providing unique insights into a wide range of issues affecting women and girls.
Researchers from the Center on Gender Equity and Health at the University of California at San Diego (UC San Diego) have undertaken a series of briefs that analyze big data — such as, Twitter data and Google Trends — to highlight key gendered issues during the pandemic within select country contexts and to offer a “how-to” section for replication of these analyses in any country context. For each brief in the five-part series, researchers provide reproducible codes along with a description of the methodology. Briefs will be published once a month. This work was supported by a grant to UC San Diego from the Bill and Melinda Gates Foundation.