Abstract
In the past few years, research about event detection has been devoted to a lot. In this paper, we propose an efficient method to detect hot events that spread within social media. Specifically, we build a directed weighted graph of words named EventGraph, in which events are embedded in the form of sub-graphs or communities. Lastly, we put forward a key node based event community detection method, which improve the efficiency of graph based event detection algorithms.
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Acknowledgments
This work is partially supported by the National Natural Science Foundation of China (NO.61272147) and the Planned Science and Technology Project of Changsha City (No. KC17010266).
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He, J., Liu, Y., Jia, Y. (2018). EventGraph Based Events Detection in Social Media. In: Zhou, Q., Miao, Q., Wang, H., Xie, W., Wang, Y., Lu, Z. (eds) Data Science. ICPCSEE 2018. Communications in Computer and Information Science, vol 902. Springer, Singapore. https://doi.org/10.1007/978-981-13-2206-8_14
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DOI: https://doi.org/10.1007/978-981-13-2206-8_14
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