开源工具库，一键实现社交事件检测与分析
SocialED: A Python Library for Social Event Detection
- 集成19种算法与14个数据集，统一接口支持多任务
- 支持图构建、分词等预处理，兼容主流深度学习框架
- 适合研究者快速实验，也适合开发人员部署应用
SocialED 是一个全面的开源 Python 工具库，用于支持社交事件检测（SED）任务，整合了19种检测算法和14个多样化数据集。它提供统一 API 和详细文档，为研究人员和实践者提供社交媒体事件检测的完整解决方案。该库设计注重模块化，支持用户灵活调整和扩展组件以适应不同场景。SocialED 支持多种预处理技术，如图构建与分词，并提供标准化的模型训练与预测接口。通过集成主流深度学习框架，确保在 CPU 与 GPU 环境下的高效性与可扩展性。代码遵循高标准，包含单元测试、持续集成与代码覆盖率，保障软件稳健可靠。SocialED 已公开发布于 <https://github.com/RingBDStack/SocialED>，可通过 PyPI 安装使用。
原文摘要 · Abstract (English)
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.
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