# Shirtless and Dangerous: Quantifying Linguistic Signals of Gender Bias in an Online Fiction Writing Community

arXiv: https://arxiv.org/abs/1603.08832 · HTML: https://mlsanity.com/paper/1603.08832/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Mar 2016.

## Built on by (most cited first, 21 of 21)

- [Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies](https://mlsanity.com/paper/2108.12084/) (2021)
- [A Survey on Gender Bias in Natural Language Processing](https://mlsanity.com/paper/2112.14168/) (2021)
- [Uncovering Implicit Gender Bias in Narratives through Commonsense Inference](https://mlsanity.com/paper/2109.06437/) (2021)
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- [The Emotion Dynamics of Literary Novels](https://mlsanity.com/paper/2403.02474/) (2024)
- [The GPT-WritingPrompts Dataset: A Comparative Analysis of Character Portrayal in Short Stories](https://mlsanity.com/paper/2406.16767/) (2024)
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- [How Prevalent is Gender Bias in ChatGPT? -- Exploring German and English ChatGPT Responses](https://mlsanity.com/paper/2310.03031/) (2023)
- [Leveraging Large Language Models to Measure Gender Representation Bias in Gendered Language Corpora](https://mlsanity.com/paper/2406.13677/) (2024)
- [Spacerini: Plug-and-play Search Engines with Pyserini and Hugging Face](https://mlsanity.com/paper/2302.14534/) (2023)
- [Show, Don't Tell: Uncovering Implicit Character Portrayal using LLMs](https://mlsanity.com/paper/2412.04576/) (2024)
- [CO-STAR: Conceptualisation of Stereotypes for Analysis and Reasoning](https://mlsanity.com/paper/2112.00819/) (2021)
- [Personality Shapes Gender Bias in Persona-Conditioned LLM Narratives Across English and Hindi: An Empirical Investigation](https://mlsanity.com/paper/2604.23600/) (2026)
- [Revisiting The Classics: A Study on Identifying and Rectifying Gender Stereotypes in Rhymes and Poems](https://mlsanity.com/paper/2403.11752/) (2024)
- [A Holistic Indicator of Polarization to Measure Online Sexism](https://mlsanity.com/paper/2404.02205/) (2024)
- [A Survey of Text Style Transfer: Applications and Ethical Implications](https://mlsanity.com/paper/2407.16737/) (2024)
- [Capturing Differences in Character Representations Between Communities: An Initial Study with Fandom](https://mlsanity.com/paper/2409.11170/) (2024)

## Abstract (arXiv)

Imagine a princess asleep in a castle, waiting for her prince to slay the dragon and rescue her. Tales like the famous Sleeping Beauty clearly divide up gender roles. But what about more modern stories, borne of a generation increasingly aware of social constructs like sexism and racism? Do these stories tend to reinforce gender stereotypes, or counter them? In this paper, we present a technique that combines natural language processing with a crowdsourced lexicon of stereotypes to capture gender biases in fiction. We apply this technique across 1.8 billion words of fiction from the Wattpad online writing community, investigating gender representation in stories, how male and female characters behave and are described, and how authors' use of gender stereotypes is associated with the community's ratings. We find that male over-representation and traditional gender stereotypes (e.g., dominant men and submissive women) are common throughout nearly every genre in our corpus. However, only some of these stereotypes, like sexual or violent men, are associated with highly rated stories. Finally, despite women often being the target of negative stereotypes, female authors are equally likely to write such stereotypes as men.