Information Dissemination Mechanism Based on Cloud Computing Cross-Media Public Opinion Network Environment

2021 ◽  
Vol 14 (2) ◽  
pp. 70-83
Author(s):  
Ping Liu
Keyword(s):  
Cloud Computing ◽  
Public Opinion ◽  
Computer Technology ◽  
Information Dissemination ◽  
Transmission Mechanism ◽  
Practical Significance ◽  
Propagation Mechanism ◽  
Cross Media ◽  
User Density ◽  
Network Public Opinion

As an important expression of social public opinion, network public opinion develops rapidly with the popularization of the internet and then affects the real society. Therefore, the use of computer technology to study the network public opinion information transmission mechanism has strong practical significance. The purpose of this paper is to use cloud computing to realize the research of information dissemination mechanism in the context of cross-media public opinion network. Researched from three aspects of operator supervision, number of media, and user density, the hotspot propagation mechanism of Storm platform given in this paper can solve the efficiency problems of traditional algorithms while ensuring accuracy, improve efficiency, and lay the foundation for the research on the monitoring of Internet public opinion propagation.

Information Propagation and Public Opinion Evolution Model Based on Artificial Neural Network in Online Social Network

2019 ◽  
Vol 63 (11) ◽  
pp. 1689-1703 ◽  
Author(s):  
Xiaoyang Liu ◽  
Daobing He
Keyword(s):  
Neural Network ◽  
Public Opinion ◽  
Social Network ◽  
Information Dissemination ◽  
Online Social Network ◽  
Information Propagation ◽  
Propagation Algorithm ◽  
Information Interaction ◽  
Opinion Evolution ◽  
Network Public Opinion

Abstract This paper proposes a new information dissemination and opinion evolution IPNN (Information Propagation Neural Network) model based on artificial neural network. The feedforward network, feedback network and dynamic evolution algorithms are designed and implemented. Firstly, according to the ‘six degrees separation’ theory of information dissemination, a seven-layer neural network underlying framework with input layer, propagation layer and termination layer is constructed; secondly, the information sharing and information interaction evolution process between nodes are described by using the event information forward propagation algorithm, opinion difference reverse propagation algorithm; finally, the external factors of online social network information dissemination is considered, the impact of external behavior patterns is measured by media public opinion guidance and network structure dynamic update operations. Simulation results show that the proposed new mathematical model reveals the relationship between the state of micro-network nodes and the evolution of macro-network public opinion. It accurately depicts the internal information interaction mechanism and diffusion mechanism in online social network. Furthermore, it reveals the process of network public opinion formation and the nature of public opinion explosion in online social network. It provides a new scientific method and research approach for the study of social network public opinion evolution.

scholarly journals Network public opinion propagation model based on the influence of media and interpersonal communication

2019 ◽  
Vol 33 (32) ◽  
pp. 1950393 ◽  
Author(s):  
Yue-Xia Zhang ◽  
Yi-Xuan Feng ◽  
Rui-Qi Yang
Keyword(s):  
Public Opinion ◽  
Interpersonal Relationships ◽  
Media Coverage ◽  
Rapid Development ◽  
Propagation Model ◽  
Practical Significance ◽  
Seir Model ◽  
Model Based ◽  
The Impact ◽  
Network Public Opinion

With the rapid development of the Internet, social media networks have become the primary platform for people to express their views. In addition, network public opinion has a considerable influence on society. Thus, considering the significant impact of online public opinion on society, it is necessary to study and analyze the propagation process for public opinion. In this study, we propose the Media and Interpersonal Relationship-SEIR (MI-SEIR) model based on the SEIR model. Our proposed model considers the impact of media transmission and interpersonal relationships on opinion propagation. Our MI-SEIR model divides the propagation nodes into three categories: support, neutral and opposition. There is a discussion mechanism between these nodes that represents the node’s viewpoint value evolution rule based on the node firmness, influence of nodes, quality of media coverage and parameters of infection. The state transition of nodes is decided based on the change of opinion value. Our simulation experimental results show that this model is more representative of the real propagation of online public opinion and is thus of practical significance for research and opinion analysis applications.

Deep Structured Learning for Natural Language Processing

2021 ◽  
Vol 20 (3) ◽  
pp. 1-14
Author(s):  
Yong Li ◽  
Xiaojun Yang ◽  
Min Zuo ◽  
Qingyu Jin ◽  
Haisheng Li ◽  
...  
Keyword(s):  
Public Opinion ◽  
Food Safety ◽  
Language Processing ◽  
Early Warning ◽  
Conditional Random Field ◽  
Semantic Features ◽  
Related Sequence ◽  
The Public ◽  
Network Public Opinion

The real-time and dissemination characteristics of network information make net-mediated public opinion become more and more important food safety early warning resources, but the data of petabyte (PB) scale growth also bring great difficulties to the research and judgment of network public opinion, especially how to extract the event role of network public opinion from these data and analyze the sentiment tendency of public opinion comment. First, this article takes the public opinion of food safety network as the research point, and a BLSTM-CRF model for automatically marking the role of event is proposed by combining BLSTM and conditional random field organically. Second, the Attention mechanism based on vocabulary in the field of food safety is introduced, the distance-related sequence semantic features are extracted by BLSTM, and the emotional classification of sequence semantic features is realized by using CNN. A kind of Att-BLSTM-CNN model for the analysis of public opinion and emotional tendency in the field of food safety is proposed. Finally, based on the time series, this article combines the role extraction of food safety events and the analysis of emotional tendency and constructs a net-mediated public opinion early warning model in the field of food safety according to the heat of the event and the emotional intensity of the public to food safety public opinion events.

Conditions for the development of the philosophy of non-violence in the modern world

2020 ◽  
pp. 337-352
Author(s):  
Tolganay V. Mustafina-Kulchmanova ◽  
Zhabayhan M. Abdildin ◽  
Kudaibergen A. Temirgaliev ◽  
Kuralay S. Yermagambetova ◽  
Manifa S. Sarkulova
Keyword(s):  
Public Opinion ◽  
Comparative Study ◽  
Political Science ◽  
Practical Significance ◽  
Modern World ◽  
Practical Application ◽  
Theoretical Methods ◽  
University Teachers ◽  
Analysis And Synthesis ◽  
And Behavior

This article addresses the issues of the genesis of non-violence and the practical application of non-violent practices in the context of modern realities. The phe-nomenon of non-violence is seen in close connection with violence, which is more often reflected in the form of wars, military clashes, and conflicts. The article pro-vides an analysis of the use of non-violent practices and the possibility of develop-ing peacekeeping in public opinion and behavior. During the preparation of this article, a review and comparative study of various literature aimed at studying non-violence were carried out. Together with the philosophical works, various ma-terials of a political science character are studied. In preparing this work, they were used as general theoretical methods, such as analysis and synthesis. At the same time, analogies, systematization, etc. were used. The materials of the article sug-gest practical significance for university teachers of humanitarian/philosophical specialties.

Sign in / Sign up

Export Citation Format

Share Document