# DeepTingle

arXiv: https://arxiv.org/abs/1705.03557 · HTML: https://mlsanity.com/paper/1705.03557/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 May 2017.

## Built on by (most cited first, 11 of 11)

- [Designing Creative AI Partners with COFI: A Framework for Modeling Interaction in Human-AI Co-Creative Systems](https://mlsanity.com/paper/2204.07666/) (2022)
- [Inferring the Reader: Guiding Automated Story Generation with Commonsense Reasoning](https://mlsanity.com/paper/2105.01311/) (2021)
- [Creating Suspenseful Stories: Iterative Planning with Large Language Models](https://mlsanity.com/paper/2402.17119/) (2024)
- [Inspiration through Observation: Demonstrating the Influence of Automatically Generated Text on Creative Writing](https://mlsanity.com/paper/2107.04007/) (2021)
- [Goal-Directed Story Generation: Augmenting Generative Language Models with Reinforcement Learning](https://mlsanity.com/paper/2112.08593/) (2021)
- [Robust Preference Learning for Storytelling via Contrastive Reinforcement Learning](https://mlsanity.com/paper/2210.07792/) (2022)
- [Telling Stories through Multi-User Dialogue by Modeling Character Relations](https://mlsanity.com/paper/2105.15054/) (2021)
- [Guiding Neural Story Generation with Reader Models](https://mlsanity.com/paper/2112.08596/) (2021)
- [Fabula Entropy Indexing: Objective Measures of Story Coherence](https://mlsanity.com/paper/2104.07472/) (2021)
- [Automated Story Generation as Question-Answering](https://mlsanity.com/paper/2112.03808/) (2021)
- [Nonslop: A Gamified Experiment in Human-AI Collaborative Writing](https://mlsanity.com/paper/2606.12350/) (2026)

## Abstract (arXiv)

DeepTingle is a text prediction and classification system trained on the collected works of the renowned fantastic gay erotica author Chuck Tingle. Whereas the writing assistance tools you use everyday (in the form of predictive text, translation, grammar checking and so on) are trained on generic, purportedly "neutral" datasets, DeepTingle is trained on a very specific, internally consistent but externally arguably eccentric dataset. This allows us to foreground and confront the norms embedded in data-driven creativity and productivity assistance tools. As such tools effectively function as extensions of our cognition into technology, it is important to identify the norms they embed within themselves and, by extension, us. DeepTingle is realized as a web application based on LSTM networks and the GloVe word embedding, implemented in JavaScript with Keras-JS.