Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships

@inproceedings{Iyyer2016FeudingFA,
  title={Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships},
  author={Mohit Iyyer and Anupam Guha and Snigdha Chaturvedi and Jordan L. Boyd-Graber and Hal Daum{\'e}},
  booktitle={HLT-NAACL},
  year={2016}
}
Understanding how a fictional relationship between two characters changes over time (e.g., from best friends to sworn enemies) is a key challenge in digital humanities scholarship. We present a novel unsupervised neural network for this task that incorporates dictionary learning to generate interpretable, accurate relationship trajectories. While previous work on characterizing literary relationships relies on plot summaries annotated with predefined labels, our model jointly learns a set of… CONTINUE READING
Highly Cited
This paper has 43 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 33 extracted citations

Extraction of Relationship Between Characters in Narrative Summaries

2018 International Conference on Emerging Trends and Innovations In Engineering And Technological Research (ICETIETR) • 2018

References

Publications referenced by this paper.
Showing 1-10 of 43 references

Similar Papers

Loading similar papers…