Contributors

Abstract

Books have the power to make us feel happiness, sadness, pain, surprise, or sorrow. An author's dexterity in the use of these emotions captivates readers and makes it difficult for them to put the book down. In this paper, we model the flow of emotions over a book using recurrent neural networks and quantify its usefulness in predicting success in books. We obtained the best weighted F1-score of 69% for predicting books' success in a multitask setting (simultaneously predicting success and genre of books).

Source code and Data

https://github.com/sjmaharjan/emotion_flow

Read the paper

http://www.aclweb.org/anthology/N18-2042

Cite the paper using

@InProceedings{maharjan-EtAl:2018:N18-2,
  author    = {Maharjan, Suraj  and  Kar, Sudipta  and  Montes, Manuel  and  Gonzalez, Fabio A.  and  Solorio, Thamar},
  title     = {Letting Emotions Flow: Success Prediction by Modeling the Flow of Emotions in Books},
  booktitle = {Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {259--265},
  abstract  = {Books have the power to make us feel happiness, sadness, pain, surprise, or sorrow. An author's dexterity in the use of these emotions captivates readers and makes it difficult for them to put the book down. In this paper, we model the flow of emotions over a book using recurrent neural networks and quantify its usefulness in predicting success in books. We obtained the best weighted F1-score of 69% for predicting books' success in a multitask setting (simultaneously predicting success and genre of books).},
  url       = {http://www.aclweb.org/anthology/N18-2042}
}

For any query, please contact the first author smaharjan2 AT uh DOT edu.