Quantitative Text Analysis: Supervised Methods and Text Classification (few places remaining)
Date:
28/05/2013
Organised by:
London School of Economics and Political Science
Presenter:
Professor Kenneth Benoit
Level:
Intermediate (some prior knowledge)
Contact:
John Fyson j.a.fyson@lse.ac.uk
Location:
View in Google Maps (WC2A 2AE)
Venue:
London School of Economics and Political Science, Houghton Street, London
This topic introduces methods for placing documents on continuous dimensions or ‘scales’, using a semi-supervised approach method known as Wordscores. This algorithmic applies a probability model of words given texts that can be used to estimate their characteristics along a latent dimension. We then generalize this method to the Naïve Bayes classifier, a method that permits the automatic classification of texts in a test set following machine learning from a training set.
Readings:
- Manning, Raghavan, and Schütze (2009, Chapter 13)â�¨Statsoft, “Naive Bayes Classifier Introductory Overview,” http://www.statsoft.com/textbook/ naive-bayes-classifier/.â�¨
- Bionicspirit.com, 9 Feb 2012, “How to Build a Naive Bayes Classifier,” http://bionicspirit. com/blog/2012/02/09/howto-build-naive-bayes-classifier.html.
- An online article by Paul Graham on classifying spam e-mail. http://www.paulgraham.com/spam.html
Cost:
Free
Website and registration:
Region:
Greater London
Keywords:
Quantitative Data Handling and Data Analysis, Quantitative Software, Quantitative Text Analysis , Text Analysis , Supervised Methods , Text Classification
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