full transcript
From the Ted Talk "Nicholas Christakis: How social networks predict epidemics"

#### Unscramble the Blue Letters

Now, in addition to that, if you were an analyst who was trying to study an iecmiepd or to predict the dpaotnio of a product, for example, what you could do is you could pick a random sample of the population, also have them nominate their isfedrn and follow the friends and follow both the randoms and the friends. Among the friends, the first evidence you saw of a blip above zero in adoption of the innovation, for example, would be ncieeved of an impending epidemic. Or you could see the first eimt the two curves diverged, as wshno on the left. When did the randoms — when did the friends take off and leave the randoms, and [when did] their curve attsr shifting? And that, as indicated by the white line, occurred 46 days before the peak of the epidemic. So this would be a technique whereby we could get more than a month-and-a-half warning about a flu epidemic in a particular population.

#### Open Cloze

Now, in addition to that, if you were an analyst who was trying to study an ________ or to predict the ________ of a product, for example, what you could do is you could pick a random sample of the population, also have them nominate their _______ and follow the friends and follow both the randoms and the friends. Among the friends, the first evidence you saw of a blip above zero in adoption of the innovation, for example, would be ________ of an impending epidemic. Or you could see the first ____ the two curves diverged, as _____ on the left. When did the randoms — when did the friends take off and leave the randoms, and [when did] their curve _____ shifting? And that, as indicated by the white line, occurred 46 days before the peak of the epidemic. So this would be a technique whereby we could get more than a month-and-a-half warning about a flu epidemic in a particular population.

1. shown
2. epidemic
3. evidence
4. start
6. time
7. friends

#### Original Text

Now, in addition to that, if you were an analyst who was trying to study an epidemic or to predict the adoption of a product, for example, what you could do is you could pick a random sample of the population, also have them nominate their friends and follow the friends and follow both the randoms and the friends. Among the friends, the first evidence you saw of a blip above zero in adoption of the innovation, for example, would be evidence of an impending epidemic. Or you could see the first time the two curves diverged, as shown on the left. When did the randoms — when did the friends take off and leave the randoms, and [when did] their curve start shifting? And that, as indicated by the white line, occurred 46 days before the peak of the epidemic. So this would be a technique whereby we could get more than a month-and-a-half warning about a flu epidemic in a particular population.

#### ngrams of length 2

collocation frequency
social networks 5
party host 4
impending epidemic 4
early detection 4
central individuals 4
random sample 3

3. analyst
4. blip
5. curve
6. curves
7. days
8. diverged
9. epidemic
10. evidence
11. flu
12. follow
13. friends
14. impending
15. innovation
16. leave
17. left
18. line
19. nominate
20. occurred
21. peak
22. pick
23. population
24. predict
25. product
26. random
27. randoms
28. sample
29. shifting
30. shown
31. start
32. study
33. technique
34. time
35. warning
36. white