Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (7): 118-123.doi: 10.11896/jsjkx.200600155

• Database & Big Data & Data Science • Previous Articles     Next Articles

Prediction of Evolution Trend of Online Public Opinion Events Based on Attention Mechanism in Social Networks

SANG Chun-yan1, XU Wen1, JIA Chao-long1, WEN Jun-hao2   

  1. 1 School of Software Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China
    2 School of Big Data & Software Engineering,Chongqing University,Chongqing 401331,China
  • Received:2020-06-24 Revised:2020-10-09 Online:2021-07-15 Published:2021-07-02
  • About author:SANG Chun-yan,born in 1983,Ph.D,associate professor.Her main research interests include service recommendation and data mining.
  • Supported by:
    National Natural Science Foundation of China(61672117) and Research project of Chongqing CSTC(cstc2019jcyj-msxmX0588).

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Abstract: Compared with traditional media,social networks play a prominent role in disseminating news,ideas,and opinions,and are also the best way to spread negative information such as rumors and false news.Therefore,accurate prediction and effective control of the evolution trend of online public opinion have become important research topics.At present,most studies predict the evolution characteristics and development trends of online public opinion events from the perspective of theoretical modeling.The modeling and analysis of information dissemination evolution trend prediction models based on user behavior characteristics need to be further studied.Considering the interaction between users in the process of information dissemination,this paper proposes a method based on the attention mechanism,which aims to explore the evolution trend prediction of information dissemination in social networks.Firstly,a network architecture based on long shot-term memory (LSTM) is used to obtain the trajectory characteristics of information propagation.Secondly,considering the complexity of information dissemination and user behavior,the attention mechanism is used to mine the dependence between users to predict the real information dissemination process.Finally,we comprehensively consider the driving factors that affect information dissemination,and obtain an attention diffusion neural network (ADNN) based on the attention mechanism.The experimental results on the four comparative data sets show that the ADNN model is better than the popular sequence model.This model can effectively use the influence of driving factors on information dissemination,and more accurately predict the trend of information dissemination in social networks.

Key words: Attention mechanism, Deep learning, Information dissemination, Trend prediction

CLC Number: 

  • TP311
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