Twitter Data-Mini Project

Transcript

1. Data Mini-Project Nitin Jain Pavan Kumar Geoffrey Jacoby Abhishek Nandakumar

2. None

3. 151.78240 35.45195 68.79268 79.56177

4. p-value ~ 1.7e−18

5. ordinary people hollywood stars

6. “I want”

7. San Francisco Memphis Things for Christmas Something (describe it) Someone

   (to do something) Ice Cream Love Things for Christmas Money Pizza Someone (to do something..) (Some kind of) House

8. words common to SF + Memphis p-value = 0.127 Difference

   insignificant.

9. all unique words p-value = 3.17e−07 Difference meaningful.

10. Potential confounds Wants for Christmas. ! Words occurring once. !

    Context changes meaning: ! I seriously think I want to hire someone to brush my hair for me after I get out of the shower. DAMN. So many tangles. #lazy ! I want someone to fall in love with the way I laugh and fall in love with my smile.

11. Follower Count Following Count Listed (count) Tweet count URLs in

    100 most recent tweets Gender 118 celebrities
12. None

13. Outliers

14. Barack Obama Arnold Schwarzenegger Al Gore Senator John Mccain Sarah

    Palin Hillary Clinton John Boehner Joe Biden Politicians 40,185,454 2,925,511 2,701,171 1,849,471 998,646 945,905 585,267 519,641

15. Tim O’Reilly Deepak Chopra Guy Kawasaki John C. Maxwell Beth

    Kanter Authors 1,736,824 1,694,682 1,395,960 869,970 403,402

16. Kaka Shaquille O' Neal Lance Armstrong Rubens Barrichello Mark Sanchez

    Sports 17,452,018 7,843,305 3,918,367 2,020,439 832,289
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19. 118 → 68 celebrities Linear model found variables significant.

20. Adjusted R2: 0.5444 ! p-values ! Number of Following 0.00892

    Number of Tweets 0.02422 Public List Appearance 2.39e−10)

21. Margin of error above 10% ! Sampling bias ! Missed

    features Time since on Twitter Rise in popularity because of recent event Issues