Helpful links/papers (please add if you find more):

1. Multilabel classification and EDA

   • https://towardsdatascience.com/journey-to-the-center-of-multi-label-classification-384c40229bff
   • http://www.davidsbatista.net/blog/2017/04/01/document_classification/

2. Random Forest Classification

   • https://www.datacamp.com/community/tutorials/random-forests-classifier-python

3. Multilabel with neural nets

   • https://www.depends-on-the-definition.com/guide-to-multi-label-classification-with-neural-networks/
   • https://medium.com/huggingface/multi-label-text-classification-using-bert-the-mighty-transformer-69714fa3fb3d

4. Emotion classification

   • Emotion intensities in tweets: https://arxiv.org/pdf/1708.03696.pdf
   • Detecting emotions in twitter messages: http://web.cs.wpi.edu/~emmanuel/publications/PDFs/C30.pdf
   • SemEval winning team paper and model: https://arxiv.org/pdf/1804.06658.pdf, https://github.com/cbaziotis/ntua-slp-semeval2018

5. Class Activation Maps (Visualization)

   • https://raghakot.github.io/keras-vis/visualizations/class_activation_maps/
   • https://arxiv.org/pdf/1710.11063.pdf