TY - GEN
T1 - SocialED
T2 - 9th Asia-Pacific Web and Web-Age Information Management Joint International Conference on Web and Big Data, APWeb-WAIM 2025
AU - Zhang, Kun
AU - Yu, Xiaoyan
AU - Li, Pu
AU - Peng, Hao
AU - Yu, Philip S.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
PY - 2026
Y1 - 2026
N2 - SocialED is a comprehensive, open-source Python library for social event detection (SED), integrating 19 algorithms and 15 datasets under a unified, modular API. It supports diverse preprocessing techniques (e.g., graph construction, tokenization) and provides standardized interfaces for training and inference. Designed for extensibility and efficiency, SocialED is compatible with popular deep learning frameworks and runs smoothly on both CPU and GPU. The library emphasizes code quality through unit testing, CI, and coverage checks. It is available at https://github.com/RingBDStack/SocialED and installable via PyPI. It has gained significant attention, with more than 580 stars on GitHub and over 18,000 PyPI downloads.
AB - SocialED is a comprehensive, open-source Python library for social event detection (SED), integrating 19 algorithms and 15 datasets under a unified, modular API. It supports diverse preprocessing techniques (e.g., graph construction, tokenization) and provides standardized interfaces for training and inference. Designed for extensibility and efficiency, SocialED is compatible with popular deep learning frameworks and runs smoothly on both CPU and GPU. The library emphasizes code quality through unit testing, CI, and coverage checks. It is available at https://github.com/RingBDStack/SocialED and installable via PyPI. It has gained significant attention, with more than 580 stars on GitHub and over 18,000 PyPI downloads.
KW - Graph Neural Networks
KW - Python Libraries
KW - Social Event Detection
UR - https://www.scopus.com/pages/publications/105029818454
U2 - 10.1007/978-981-95-5722-6_22
DO - 10.1007/978-981-95-5722-6_22
M3 - 会议稿件
AN - SCOPUS:105029818454
SN - 9789819557219
T3 - Lecture Notes in Computer Science
SP - 255
EP - 260
BT - Web and Big Data - 9th International Joint Conference, APWeb-WAIM 2025, Proceedings
A2 - Li, Jiajia
A2 - Chbeir, Richard
A2 - Li, Lei
A2 - Zong, Chuanyu
A2 - Zhang, Yanfeng
A2 - Zhang, Mengxuan
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 28 August 2025 through 30 August 2025
ER -