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 \url{https://github.com/RingBDStack/SocialED} and can be installed via PyPI.

翻译：SocialED是一个全面的开源Python库，旨在支持社交事件检测任务，集成了19种检测算法和14个多样化数据集。它提供了具有详细文档的统一API，为研究人员和从业者提供了社交媒体事件检测的完整解决方案。该库采用模块化设计，允许用户轻松适应和扩展组件以应对各种用例。SocialED支持广泛的预处理技术，如图构建和分词，并包含用于训练模型和进行预测的标准化接口。通过集成流行的深度学习框架，SocialED确保了在CPU和GPU环境下的高效性和可扩展性。该库遵循高代码质量标准构建，包括单元测试、持续集成和代码覆盖率，确保SocialED提供稳健、可维护的软件。SocialED公开发布于\url{https://github.com/RingBDStack/SocialED}，并可通过PyPI安装。