# SocialED: A Python Library for Social Event Detection

arXiv: https://arxiv.org/abs/2412.13472 · HTML: https://mlsanity.com/paper/2412.13472/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 41 references that are in the map.
- First posted on arXiv 18 Dec 2024.

## Builds on (most cited first, 2 of 2)

- [HuggingFace's Transformers: State-of-the-art Natural Language Processing](https://mlsanity.com/paper/1910.03771/) (2019)
- [A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria](https://mlsanity.com/paper/1805.05144/) (2018)

## Abstract (arXiv)

SocialED is a comprehensive, open-source Python library designed to support social event detection (SED) tasks, integrating 19 detection algorithms and 14 diverse datasets. It provides a unified API with detailed documentation, offering researchers and practitioners a complete solution for event detection in social media. The library is designed with modularity in mind, allowing users to easily adapt and extend components for various use cases. SocialED supports a wide range of preprocessing techniques, such as graph construction and tokenization, and includes standardized interfaces for training models and making predictions. By integrating popular deep learning frameworks, SocialED ensures high efficiency and scalability across both CPU and GPU environments. The library is built adhering to high code quality standards, including unit testing, continuous integration, and code coverage, ensuring that SocialED delivers robust, maintainable software. SocialED is publicly available at urlhttps://github.com/RingBDStack/SocialED and can be installed via PyPI.