1. Example analysis of tweets using Python text analytic tools

2. Text analytics with Python
Preview of hands-on experience using Python and Python Libraries to analyze sample tweets
Goal is not to teach programming, but to illustrate in a hands-on how these processes work
Understand where and how they may be useful
Potential use cases
Roughly what is involved in analyzing

3. Supervised machine learning…

4. Can you spot the sea cow

5. Can you spot the sea cow

6. On to text…
Can use similar approach to analyze text, where your expertise identifies the type of categorization
OR one where you let the computer do more of the exploring—’unsupervised machine learning’
Haven’t predefined what is right—doing ‘unsupervised learning’ to see what groupings are
But we still involve human judgment, as you will see
Example analysis of tweets re Haiti and Cholera

7. Text analytics schematic
#Haiti has begun a large-scale vaccination campaign to battle a #cholera
haiti has begun a large-scale vaccination campaign to battle a cholera
‘haiti’ ‘ has’ ‘begun’ ‘a’ ‘large-scale’ ‘vaccination’
‘haiti’ ‘ has’ ‘begun’ ‘a’ ‘large-scale’ ‘vaccination’
‘haiti’ ‘ has’ ‘begun’ ‘a’ ‘large-scale’ ’vaccination’

8. Jupyter helps communicate

9. Clean the data…

10. Stop words and phrase length

11. Word clouds illustrate topics
**Just the beginning….
Can trend and track over time, combine with other data

12. Python
Notebook
Breakout
12/14/2016