# A City of Millions: Mapping Literary Social Networks At Scale

arXiv: https://arxiv.org/abs/2502.19590 · HTML: https://mlsanity.com/paper/2502.19590/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 46 references that are in the map.
- First posted on arXiv 26 Feb 2025.

## Builds on (most cited first, 11 of 11)

- [RoFormer: Enhanced Transformer with Rotary Position Embedding](https://mlsanity.com/paper/2104.09864/) (2021)
- [Gemma 2: Improving Open Language Models at a Practical Size](https://mlsanity.com/paper/2408.00118/) (2024)
- [SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing](https://mlsanity.com/paper/1808.06226/) (2018)
- [Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation](https://mlsanity.com/paper/2403.06988/) (2024)
- [The emotional arcs of stories are dominated by six basic shapes](https://mlsanity.com/paper/1606.07772/) (2016)
- [Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characters](https://mlsanity.com/paper/1903.12453/) (2019)
- [Large Language Models Fall Short: Understanding Complex Relationships in Detective Narratives](https://mlsanity.com/paper/2402.11051/) (2024)
- [Annotating Character Relationships in Literary Texts](https://mlsanity.com/paper/1512.00728/) (2015)
- [Mining and modeling character networks](https://mlsanity.com/paper/1608.00646/) (2016)
- [Temporal Embeddings and Transformer Models for Narrative Text Understanding](https://mlsanity.com/paper/2003.08811/) (2020)
- [Social network analysis of manga: similarities to real-world social networks and trends over decades](https://mlsanity.com/paper/2303.07208/) (2023)

## Built on by (most cited first, 2 of 2)

- [Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A Survey](https://mlsanity.com/paper/2602.15851/) (2026)
- [Computational Representations of Character Significance in Novels](https://mlsanity.com/paper/2601.15508/) (2026)

## Abstract (arXiv)

We release 70,509 high-quality social networks extracted from multilingual fiction and nonfiction narratives. We additionally provide metadata for ~30,000 of these texts (73% nonfiction and 27% fiction) written between 1800 and 1999 in 58 languages. This dataset provides information on historical social worlds at an unprecedented scale, including data for 2,510,021 individuals in 2,805,482 pair-wise relationships annotated for affinity and relationship type. We achieve this scale by automating previously manual methods of extracting social networks; specifically, we adapt an existing annotation task as a language model prompt, ensuring consistency at scale with the use of structured output. This dataset serves as a unique resource for humanities and social science research by providing data on cognitive models of social realities.