Using Search Queries to Understand Health Information Needs in Africa
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Abstract (arXiv)
The lack of comprehensive, high-quality health data in developing nations creates a roadblock for combating the impacts of disease. One key challenge is understanding the health information needs of people in these nations. Without understanding people's everyday needs, concerns, and misconceptions, health organizations and policymakers lack the ability to effectively target education and programming efforts. In this paper, we propose a bottom-up approach that uses search data from individuals to uncover and gain insight into health information needs in Africa. We analyze Bing searches related to HIV/AIDS, malaria, and tuberculosis from all 54 African nations. For each disease, we automatically derive a set of common search themes or topics, revealing a wide-spread interest in various types of information, including disease symptoms, drugs, concerns about breastfeeding, as well as stigma, beliefs in natural cures, and other topics that may be hard to uncover through traditional surveys. We expose the different patterns that emerge in health information needs by demographic groups (age and sex) and country. We also uncover discrepancies in the quality of content returned by search engines to users by topic. Combined, our results suggest that search data can help illuminate health information needs in Africa and inform discussions on health policy and targeted education efforts both on- and offline.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Jun 2018.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 2.
5 papers.
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- 2021Have you tried Neural Topic Models? Comparative Analysis of Neural and Non-Neural Topic Models with Application to COVID-19 Twitter Datacited by 0
- 2024Comparison of Machine Learning Classification Algorithms and Application to the Framingham Heart Studycited by 0
- 2024Auditing of AI: Legal, Ethical and Technical Approaches7 Jul 2024
- 2024Comparison of Machine Learning Classification Algorithms and Application to the Framingham Heart Study22 Feb 2024
- 2023Accurate Measures of Vaccination and Concerns of Vaccine Holdouts from Web Search Logs12 Jun 2023
- 2022Trucks Don't Mean Trump: Diagnosing Human Error in Image Analysis15 May 2022
- 2021Have you tried Neural Topic Models? Comparative Analysis of Neural and Non-Neural Topic Models with Application to COVID-19 Twitter Data21 May 2021