Word Pair Convolutional Model for Happy Moment Classification

  title={Word Pair Convolutional Model for Happy Moment Classification},
  author={Michael Saxon and Samarth Bhandari and Lewis Ruskin and Gabrielle Honda},
We propose the Word Pair Convolutional Model (WoPCoM) for the CL-Aff 19 shared task at the AAAI-19 Workshop on Affective Content Analysis. The challenge is the classification of speaker-described happy moments as social events and/or activities in which they have agency. WoPCoM leverages the regular structure of language on an architectural level in a way that recurrent models cannot easily answer, by learning convolutional word pair features that capture the important intraand inter-phrasal… CONTINUE READING

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Key Quantitative Results

  • It performs with an average accuracy of 91.45% predicting the social label and 86.49% predicting the agency label assessed on a 10-fold cross validation.

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