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Speed dating Classification “What you should know about dating”

Speed dating Classification “What you should know about dating”. Stephen Cohen Rajesh Ranganath Te Thamrongrattanarit. Speed dating. A rabbi invented speed dating 10 years ago Here’s how it works… Goal : To find the model that predicts men and women’s decisions. Massive feature extraction.

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Speed dating Classification “What you should know about dating”

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  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 • Here’s how it works… • Goal : To find the model that predicts men and women’s 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. 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… Women’s 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? What you should know about dating

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

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