Ms. Si Chen Profile

Si Chen

at Guilin Univ of Electronic Technology

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Proceedings Article | 27 November 2019 Paper

Community conflict prediction method based on spliced BiLSTM

Si Chen, Xiaodong Cai, Bo Li, Zhenzhen Hou

Proceedings Volume 11321, 113211V (2019) https://doi.org/10.1117/12.2540244

KEYWORDS: Social networks, Neural networks, Safety, Data mining

Read Abstract +

Existing community conflict prediction models usually use a single unidirectional LSTM network to process graph and word embeddings simultaneously. However，there is no temporal coherence between graph and word embeddings. And their importance for prediction is different. A community conflict prediction method based on spliced bidirectional LSTM is proposed. Firstly, two bidirectional LSTMs are utilized to process graph and word embeddings respectively to break temporal dependency. Secondly, the hidden states of the two bidirectional LSTMs are weighted. Finally, the weighted hidden states are spliced and fed into subsequent layers of the neural network to predict conflicts. Experimental results show that this method can improve the AUC value to 0.733 on the Reddit dataset, and reduce the number of iterations of training.

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