Online public opinion early warning method based on LSTM model

A network public opinion and model technology, applied in the direction of biological neural network models, alarms, special data processing applications, etc., can solve the problem of not considering the interconnection of network public opinion data, public opinion theme attributes and public opinion diffusion indicators. , low early warning accuracy and other issues

Inactive Publication Date: 2020-10-27
TIANJIN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

[0004] The current network public opinion index system has little consideration for public opinion theme attributes and public opinion diffusion indicators, which may lead to low early warning accurac

Method used

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  • Online public opinion early warning method based on LSTM model
  • Online public opinion early warning method based on LSTM model
  • Online public opinion early warning method based on LSTM model

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Example Embodiment

[0018] Embodiments of the present invention are described in further detail below in conjunction with the accompanying drawings:

[0019] A network public opinion early warning method based on LSTM model, comprising the following steps:

[0020] Related definitions:

[0021] (1) The indicator system refers to an organic whole composed of several independent and interrelated information indicators that reflect the characteristics of Internet public opinion events, and the last level indicators of the indicator system refer to the last sub-indicators of various indicators.

[0022] (2) Stuttering Segmentation is a python-based Chinese word segmentation tool, which is the most widely used Chinese word segmentation toolkit in China. The word segmentation effect is relatively good. It has three modes, namely precise mode, full mode and search engine mode.

[0023] (3) The Skip-Gram model is a model of word2vec. The function of the model predicts the surrounding words when the targ...

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Abstract

The invention relates to an online public opinion early warning method based on an LSTM model. The method is mainly characterized in that the method is based on an online public opinion early warningindex system and a long-short-term memory network model; the invention provides an index system comprising five dimensions of theme attributes, propagation and diffusion and the like. According to themethod, a Re-LSTM (Regulation Long Short Term Memory, long and short term memory network) model is provided on the basis, thus constraining the input weight of each unit in the network by using a regularization method, and replacing a tanh activation function with a softsign function. The method is reasonable in design, and compared with other classic models, the model constructed this time can improve the early warning accuracy and can better avoid the problems of gradient disappearance and overfitting.

Description

technical field [0001] The invention belongs to the field of network public opinion algorithm analysis, in particular to a network public opinion early warning method based on LSTM model (method on early warning of network public opinion based on long short termmemory model). Background technique [0002] Internet public opinion is a concentrated expression of various attitudes, emotions and opinions expressed and disseminated by netizens on public opinion events through the Internet. Among them, there is no lack of subjective speculation or even false information in the exchanged information, and the dissemination of such information on the Internet will inevitably have a huge impact on government credibility and social stability and development. How to control the development trend of network public opinion is particularly important. In short, a reasonable construction of network public opinion early warning index system and public opinion early warning model can effectiv...

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Application Information

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IPC IPC(8): G06F16/9535G06N3/04G08B31/00
CPCG06F16/9535G08B31/00G06N3/045
Inventor 马永军陈海山刘伟鑫
Owner TIANJIN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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