Health-Message-Lens-Myth-Fact-Dataset

Purpose of Dataset

This Dataset Pairs Health-related Statements — Written In The Hindi/hinglish Register Common On Whatsapp Forwards In India — With A Myth/fact Label And A Short Correction. It Targets A Specific Gap: Most Published Health-misinformation Datasets Used To Train Moderation And Fact-checking Classifiers Are Built From English-language, Western-sourced Content, Which Doesn't Match How Health Misinformation Actually Circulates In India. Whatsapp Has Over 97% Market Penetration In India (400m+ Users) And Is The Dominant Channel For Both News And Health Misinformation. A Cross-country Study Of Covid-19 Misinformation Found Health-related Claims Made Up The Largest Single Category Of Misinformation Analyzed. Separately, A Rural-india Field Study Found That A Majority Of Misinformation Posts Observed Had Already Been Fact-checked By Reputable Agencies, Yet Continued Circulating — Suggesting Existing Fact-checks Aren't Reaching The Audiences Most Exposed To This Content, Which Motivates Embedding Detection Directly In-channel Rather Than Relying On External Fact-check Links. The Dataset Spans Four Categories: Nutrition, Vaccines, Chronic_disease, And General_wellness. Each Row Includes The Statement, A Myth/fact Label, Category, And A One-sentence Correction Suitable For User-facing Display.