1. Speed dating Classification What you should know about dating Stephen Cohen Rajesh Ranganath Te Thamrongrattanarit

2. Speed dating A rabbi invented speed dating 10 years ago Heres how it works… Goal : To find the model that predicts men and womens decisions

3. Massive feature extraction Easy things Word count Count of certain words Backchannelling Post-conversation word count Question count Non-academic discussion Etc. Difficult things Latent Dirichlet Allocation Latent Semantic Analysis Various vector similarity metrics Speed of conversation Etc.

4. Classifiers and other techniques Lexical Feature Extraction Logistic Regression with linear kernel Support Vector Machines with… Linear kernel RBF kernel

5. Evaluation Principle Component Analysis For every feature we add, we capture more variance. = good sign The Rajesh Metric for evaluating models Logistic Regression and SVM work just as well. Pick the best model based on the Rajesh Metric Analyze regression coefficients of the best model

6. What you should know about dating Men are more likely to say yes if.. More positive words are uttered. [lexical features] Men and women talk about the same topics [Latent Dirichlet Allocation and Jenson-Shannon similarity] Men:women word count ratio is high Women ask more questions! [count of question marks] but opposite effect on women And more… Womens decisions can hardly be predicted by the model. (Women are hard to understand…) Women are more likely to say yes if they talk about the past. Physical appearance? Voice? Speech? Chemistry?

7. Acknowledgement Professor Dan Jurafsky (Linguistics Dept.) Professor Dan McFarland (School of Education) Stephan Stiller (Computer Science) David Hall (Symbolic Systems and CS)