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arXiv · 1511.09376

Modeling Dynamic Relationships Between Characters in Literary Novels

Snigdha Chaturvedi·Shashank Srivastava·Hal Daume III·Chris Dyer
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Abstract

Studying characters plays a vital role in computationally representing and interpreting narratives. Unlike previous work, which has focused on inferring character roles, we focus on the problem of modeling their relationships. Rather than assuming a fixed relationship for a character pair, we hypothesize that relationships are dynamic and temporally evolve with the progress of the narrative, and formulate the problem of relationship modeling as a structured prediction problem. We propose a semi-supervised framework to learn relationship sequences from fully as well as partially labeled data. We present a Markovian model capable of accumulating historical beliefs about the relationship and status changes. We use a set of rich linguistic and semantically motivated features that incorporate world knowledge to investigate the textual content of narrative. We empirically demonstrate that such a framework outperforms competitive baselines.

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Snigdha Chaturvedi, Shashank Srivastava, Hal Daume III, Chris Dyer. 2015-11-30. Modeling Dynamic Relationships Between Characters in Literary Novels. https://arxiv.org/abs/1511.09376

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