# Social Media Writing Style Fingerprint

arXiv: https://arxiv.org/abs/1712.04762 · HTML: https://mlsanity.com/paper/1712.04762/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Dec 2017.

## Built on by (most cited first, 1 of 1)

- [Assessing Capabilities of Large Language Models in Social Media Analytics: A Multi-task Quest](https://mlsanity.com/paper/2604.18955/) (2026)

## Abstract (arXiv)

We present our approach for computer-aided social media text authorship attribution based on recent advances in short text authorship verification. We use various natural language techniques to create word-level and character-level models that act as hidden layers to simulate a simple neural network. The choice of word-level and character-level models in each layer was informed through validation performance. The output layer of our system uses an unweighted majority vote vector to arrive at a conclusion. We also considered writing bias in social media posts while collecting our training dataset to increase system robustness. Our system achieved a precision, recall, and F-measure of 0.82, 0.926 and 0.869 respectively.