{"blocks": [{"key": "b00cbdcb", "text": "Scenario: Policy teams need an overnight view of fake‑news prevalence with very few human reviewers. At the same time, they want a long‑term measurement program and model improvements. You must design a rapid assessment, extrapolate platform‑level prevalence, and lay out an iterative roadmap for detection models.", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "4bb0d75f", "text": "", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "a8567d37", "text": "Question 1: With limited reviewers, how would you measure fake‑news impact within a single day? (Hint: ML pre‑labels plus targeted human sampling)", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "ced89d06", "text": "Question 2: A 1 000‑post sample shows 10 % fake news. How would you extrapolate and report the overall prevalence? (Hint: confidence intervals, weighted projection)", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "32ab185e", "text": "Question 3: Given ample resources, design a robust approach to quantify fake‑news prevalence. (Hint: stratified sampling, user exposure, propagation paths)", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "3a6256de", "text": "Question 4: Your detection model misses fake content—how would you iterate? (Hint: hard‑negative mining, active learning, ensemble models)", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}