SocialED: A Python Library for Social Event Detection

• URL: http://arxiv.org/abs/2412.13472v1
• Date: Wed, 18 Dec 2024 03:37:47 GMT
• Title: SocialED: A Python Library for Social Event Detection
• Authors: Kun Zhang, Xiaoyan Yu, Pu Li, Hao Peng, Philip S. Yu,
• Abstract summary: SocialED is a comprehensive, open-source Python library designed to support social event detection (SED) tasks. It provides a unified API with detailed documentation, offering researchers and practitioners a complete solution for event detection in social media. SocialED supports a wide range of preprocessing techniques, such as graph construction and tokenization, and includes standardized interfaces for training models and making predictions.
• Score: 53.928241775629566
• License:
• Abstract: 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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