Quantitative Text Analysis 2E, Essex 2014

Quantitative Text Analysis 2E

Essex Summer School 2014

Course handout

Instructor: Prof Kenneth Benoit, LSE

TA: Dr. Paul Nulty, LSE

Day 1: Quantitative text analysis overview and fundamentals

• slides
• demonstration .R code using US inaugural address speeches (downloaded from  https://archive.org/details/Inaugural-Address-Corpus-1789-2009)
• exercise 1 instructions and starter code
• Texts you will need for **exercise 1 – **on the S: drive

Day 2: The Elements of Textual Data

• slides
• Zipf’s law demo code in  Stata; in  R (you need your own output .csv files)
• exercise 2 instructions and starter code
• exercise 2 solution

Day 3: Descriptive Statistical Methods for Texts

• slides
• exercise 3  instructions and  starter code
• exercise 3  solution

Day 4: Quantitative methods for comparing texts

• slides
• exercise 4 instructions
• exercise 4 solution

Day 5: Automated Dictionary-Based Approaches

• slides
• exercise 5  instructions
• exercise 5 solution

Day 6: Document classifiers

• slides
• exercise 6 instructions
• exercise 6  solution

Day 7: Supervised Models for Scaling Texts

• slides
• additional slides from Tom Mitchell’s Machine Learning textbook
• exercise 7  instructions
• exercise 7  solution

Day 8:  Unsupervised scaling models for text

• slides
• exercise 8  instructions
• exercise 8  solution

Day 9: Topic Models

• slides
• exercise 9 instructions
• exercise 9 solution

Day 10: Working with Big Text Data: Twitter

• slides part 1

• slides part 2

• exercise 10 instructions

• exercise 10 solution

• You might also be interested in a large corpus of 1.6 million english tweets available from  http://cs.stanford.edu/people/alecmgo/trainingandtestdata.zip (see the general web page at  http://help.sentiment140.com/for-students), if you want to play with a large dataset.