Journal of Shandong University(Engineering Science) ›› 2019, Vol. 49 ›› Issue (2): 102-106, 115.doi: 10.6040/j.issn.1672-3961.0.2018.189

• Machine Learning & Data Mining • Previous Articles     Next Articles

A microblog rumor events detection method based on C-GRU

Lizhao LI1(),Guoyong CAI1,Jiao PAN2   

  1. 1. School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541004, Guangxi, China
    2. Guilin Kaige Information Technology Co., Ltd., Guilin 541004, Guangxi, China
  • Received:2018-05-25 Online:2019-04-20 Published:2019-04-19
  • Supported by:


A microblog rumor events detection model based on convolution-gated recurrent unit(C-GRU) was proposed. Combining the advantages of CNN and GRU, the microblog event′s posts was vectorized. By learning the features representation of the microblog windows through the convolution layer of CNN, the features of microblog windows was spliced into a sequence of window feature according to the time order, and the sequence of window feature was put into the GRU to learn feature representation of sequence for rumor events detection. Experimental results from real data sets showed that this model had better ability to rumor detection than other models based on traditional machine learning, CNN or RNN.

Key words: rumor events detection, deep learning, convolution-gated recurrent unit, window feature sequence

CLC Number: 

  • TP391.1


Rumor events detection model based on C-GRU"


Convolution extract window features"


Window feature splicing and sequence construction"


GRU learns sequence features and outputs results"

Table 1

Accuracy comparison results of different methods"

方法 Ac/%
SVM-RBF 79.75
DTC 81.25
RNN 87.25
1-LSTM 89.75
1-GRU 90.25
2-GRU 90.75
CNN 95.25
C-GRU 95.75

Table 2

Accuracy comparison"

过滤器长度 滤器个数 Ac/%
2 180 92.50
3 180 93.25
4 180 94.25
5 180 93.75
2, 3 90 94.00
3, 4 90 94.50
4, 5 90 94.75
2, 3, 4 60 94.25
3, 4, 5 60 95.75
3, 4, 5 50 95.50
3, 4, 5 70 90.25
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