A method based on SVD-PCA microblog hot event prediction

Shuhao Jiang; Jiawei Zhang; Tianyang Lu; Chuanqing Wang; Yuan Chen; Jiawei Liang; Xiaolong Zhang

doi:10.1117/12.2631864

14 April 2022 A method based on SVD-PCA microblog hot event prediction

Shuhao Jiang, Jiawei Zhang, Tianyang Lu, Chuanqing Wang, Yuan Chen, Jiawei Liang, Xiaolong Zhang

Proceedings Volume 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021); 121781V (2022) https://doi.org/10.1117/12.2631864
Event: International Conference on Signal Processing and Communication Technology (SPCT 2021), 2021, Tianjin, China

Abstract

Aiming at the problem of no standard for real-time data hotspot classification, this paper proposes a method based on SVD-PCA microblog hotspot event prediction, based on the TF-IDF algorithm to calculate keyword weights, construct a text-keyword matrix, and use SVD to generate covariance matrix, and use PCA method to reduce dimensionality to alleviate sparsity, determine the evaluation criteria of hot topics based on the amount of reading and discussion, and use logistic regression to predict. Finally, through experiments on the news data set of a news website from July 2020 to July 2021, the prediction method proposed in this paper can effectively improve the accuracy of the prediction of hot events on microblog.

Citation Download Citation

Shuhao Jiang, Jiawei Zhang, Tianyang Lu, Chuanqing Wang, Yuan Chen, Jiawei Liang, and Xiaolong Zhang "A method based on SVD-PCA microblog hot event prediction", Proc. SPIE 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021), 121781V (14 April 2022); https://doi.org/10.1117/12.2631864

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