How AI researchers used Bing search results to reveal disease knowledge gaps in Africa

Interesting use of query log analysis. Researchers aggregated HIV/AIDS related queries by African searchers to mine for patterns.

How search results suggest answers

Using topical models and natural language processing, Abebe combed through 18 months of Bing search results for all 54 nations on the African continent to assess queries related to HIV/AIDS, malaria, and tuberculosis. Automation then created categories based on subject matter. The total number of queries included in the paper were not disclosed.

The AI also categorizes words and topics most associated with specific diseases. For example, women were more interested in questions related to pregnancy or breastfeeding, while men were more interested in news stories about people who say they’ve been cured of HIV.

Search results demonstrated that women and users aged 18-24 are more concerned about stigma than other groups, and natural cure searches were highest in the 35-49 age group. Cure myths that often appear in search results include the prayers of Nigerian prophets, moringa seed oil, and garlic.

The results also highlight such questions as: “I’m HIV positive, can my boss fire me?” and “What are my legal protections?” Or “What ways can you mitigate stigma in social settings?”

Link to paper: Using Search Queries to Understand Health Information Needs in Africa

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