Transition to Adulthood for Young People with Intellectual or Developmental Disabilities: Emotion Detection and Topic Modeling

This repository contains the code for corpus-based emotion detection and NMF topic modeling.

Emotion detection

We used NRC Word-Emotion Association Lexicon for emotion identification. You can apply NRC lexicon using the get_emo_words function and then calculate emotion distribution, average emotion intensity and return the most common emotion-associated words. More details are avaliable in our paper

Topic modeling

The topic modeling is based on Non-Negative Matrix Factorization model from sklearn. See an example of its work below:

Citation

Please cite our paper as below:

@InProceedings{10.1007/978-3-031-17114-7_21,
author="Liu, Yan and Laricheva, Maria and Zhang, Chiyu and Boutet, Patrick and Chen, Guanyu and Tracey, Terence and Carenini, Giuseppe and Young, Richard",
title="Transition to Adulthood for Young People with Intellectual or Developmental Disabilities: Emotion Detection and Topic Modeling",
booktitle="Social, Cultural, and Behavioral Modeling",
year="2022",
publisher="Springer International Publishing",
isbn="978-3-031-17114-7"
}