Multi-Graph Encoder-Decoder Model for Location-Based Character Networks in Literary Narrative

Avi Bleiweiss

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Paper

Multi-Graph Encoder-Decoder Model for Location-Based Character Networks in Literary Narrative

Topics: Natural Language Processing; Neural Networks; Social Network Analysis; Visualization

In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, 790-797, 2023 , Lisbon, Portugal

Author: Avi Bleiweiss

Affiliation: BShalem Research, Sunnyvale, U.S.A.

Keyword(s): Narrative Intelligence, Geo-Location, Graph Theory, Community Discovery, Neural Networks.

Abstract: In the past decade, an extended line of research developed a broad range of methods for reasoning about narrative from a social perspective. This often revolved around transforming literary text into a character network representation. However, there remain inconsistent traits of narrative structure produced computationally by either neural language technology or network theory tools. In this paper, we propose an encoder-decoder model with a main objective to mitigate the apparent computational divergence. Our encoder novelty lies in generating hundreds of location-based network graphs to render a fine-grained narrative. We further formalize a decoder task for detecting character communities and analyze modularity and membership affiliation. Through empirical experiments, we present visualization of stages in our computational process for four literary fiction novels.

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Paper citation in several formats:

Bleiweiss, A. (2023). Multi-Graph Encoder-Decoder Model for Location-Based Character Networks in Literary Narrative. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-623-1; ISSN 2184-433X, SciTePress, pages 790-797. DOI: 10.5220/0011776400003393

@conference{icaart23,
author={Avi Bleiweiss.},
title={Multi-Graph Encoder-Decoder Model for Location-Based Character Networks in Literary Narrative},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2023},
pages={790-797},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011776400003393},
isbn={978-989-758-623-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Multi-Graph Encoder-Decoder Model for Location-Based Character Networks in Literary Narrative
SN - 978-989-758-623-1
IS - 2184-433X
AU - Bleiweiss, A.
PY - 2023
SP - 790
EP - 797
DO - 10.5220/0011776400003393
PB - SciTePress