The Research on Social Networks Public Opinion Propagation Influence Models and Its Controllability

Public opinion propagation control is one of the hot topics in contemporary social network research. With the rapid dissemination of information over the Internet, the traditional isolation and vaccination strategies can no longer achieve satisfactory results. A positive guidance technology for public opinion diffusion is urgently needed. First, based on the analysis of influence network controllability and public opinion diffusion, a positive guidance technology is proposed and a new model that supports external control is established. Second, in combination with the influence network, a public opinion propagation influence network model is designed and a public opinion control point selection algorithm(POCDNSA) is proposed. Finally, An experiment verified that this algorithm can lead to users receiving the correct guidance quickly and accurately, reducing the impact of false public opinion information; the effect of CELF is no better than that of the POCDNSA algorithm. The main reason is that the former is completely based on the diffusion cascade information contained in the training data, but does not consider the specific situation of the network structure and the diffusion of public opinion information in the closed set. thus, the effectiveness and feasibility of the algorithm is proven. The findings of this article therefore provide useful insights for the implementation of public opinion control.

Understanding Interoperability in Collaborative Network Management： the Case of Metro High School

The-increasing importance of interoperability （IOp）--reciprocal communication and accommodation among government organizations and NGOs to develop interactive policy and programming--has become an integral part of networked organizations, now utilized beyond IOps＇s emergency management origins in public administration. Using a mixed methods approach, this paper empirically examines IOp in a networked STEM （science, technology, engineering and mathematics） secondary school that includes 16 school districts and their public agency and NGO partners, particularly in its planning and operational phases. It also identifies the growing use of lOp in a number of non-emergency management settings and raises the prospects for utilizing this type of interorganizational management in the public arena.

The Study of SINA micro-blog Opinion Leaders Effect on Network Public Opinion Transmission

Opinion leaders play a critical role in network public opinion transmission, their perspectives can shape public opinion and influence policy formulation and implementation. The paper is based on SINA micro-blog, by structural equation model, as Fudan Poisoning Event for example, On the basis of in-depth analysis of opinion leaders effect on network public opinion transmission characteristics, Explore the opinion leaders on the influence of network public opinion transmission mechanism, in order to better play a role of opinion leader＇s guidance of public opinion.

Research on Public Opinion Transmission and Evolution Mechanism in Network

As the Internet continues to expand, the influence of network information on real life has gradually deepened. Research on propagation and evolution of Internet public opinion has become a hot topic. The force of intemet public opinion penetrates and influences on every aspect of the society. Compared with traditional public opinion, the network public opinion has features of immediate, multivariate and interactive, the propagation behavior has the new change compared with the traditional public opinion. In the propagation behavior of network public opinion, agenda setting is no longer an arbitrary, the influence of opinion leaders in the agenda setting becomes more and more complex and diversified. The formation time of network public opinion is short, and social influence becomes strong. Guide the public opinion to build a harmonious environment of network public opinion. Overall, our country＇ s network public opinion environment is a benign situation and steadily promoting the reforms of public policies. Although there is still a few not rational voices full of them, the network public opinion shows a general trend of positive thinking. Based on this philosophy, through the research of network public opinion dissemination and evolution mechanism, can be all-round good guidance and supervision of public opinion, building a harmonious network environment of public opinion.

Research on crisis management of enterprise network public opinion

With the arrival ofthe era from the media, the internet spread over all sectors ofsocicty, affect people＇s political, economic and cultural life. The network has become the main place, people express their views so also. And the popularity of media enables consumers to easily express their products, services and other aspects of the topic, spread on the network at breakneck speed, and other users of the attention and support, thus forming a kind of public opinion, influence The development of enterprises, which will undoubtedly bring unprecedented pressure, constant attention, coupled with people＇s comments, forwarding, dissemination media, making the crisis spread, enterprises should not reasonable, effective, will enable enterprises to establish a sense of trust collapsed, brought a negative impact to the enterprise.

Innovation of Ideological and Political Education in Colleges and Universities from the Perspective of Network Public Opinion

In today's era of rapid development of network media,network public opinion has brought great changes to people's lives.As a place of frequent network public opinion,colleges and universities create a more complex and changeable network environment.This is both an opportunity and a challenge to the ideological and political education in universities.Therefore,through a brief introduction of the connotation and characteristics of network public opinion in colleges and universities,this article explores the innovation of ideological and political education in the context of network public opinion in terms of educational concepts,contents,and methods to ensure that this education plays a positive role in the new era.

Public Sentiment Analysis of Social Security Emergencies Based on Feature Fusion Model of BERT and TextLevelGCN

At present, the emotion classification method of Weibo public opinions based on graph neural network cannot solve the polysemy problem well, and the scale of global graph with fixed weight is too large. This paper proposes a feature fusion network model Bert-TextLevelGCN based on BERT pre-training and improved TextGCN. On the one hand, Bert is introduced to obtain the initial vector input of graph neural network containing rich semantic features. On the other hand, the global graph connection window of traditional TextGCN is reduced to the text level, and the message propagation mechanism of global sharing is applied. Finally, the output vector of BERT and TextLevelGCN is fused by interpolation update method, and a more robust mapping of positive and negative sentiment classification of public opinion text of “Tangshan Barbecue Restaurant beating people” is obtained. In the context of the national anti-gang campaign, it is of great significance to accurately and efficiently analyze the emotional characteristics of public opinion in sudden social violence events with bad social impact, which is of great significance to improve the government’s public opinion warning and response ability to public opinion in sudden social security events. .

Research on Prediction of Sentiment Trend of Food Safety Public Opinion

Emotion has a nearly decisive role in behavior, which will directly affect netizens’ views on food safety public opinion events, thereby affecting the development direction of public opinion on the event, and it is of great significance for food safety network public opinion to predict emotional trends to do a good job in food safety network public opinion guidance. In this paper, the dynamic text representation method XLNet is used to generate word vectors with context-dependent dependencies to distribute the text information of food safety network public opinion. Then, the word vector is input into the CNN-BiLSTM network for local semantic feature and context semantic extraction. The attention mechanism is introduced to give different weights according to the importance of features, and the emotional tendency analysis is carried out. Based on sentiment analysis, sentiment value time series data is obtained, and a time series model is constructed to predict sentiment trends. The sentiment analysis model proposed in this paper can well classify the sentiment of food safety network public opinion, and the time series model has a good effect on the prediction of food safety network public opinion sentiment trend. .

Scheme of Railway 5G Integrated Innovation Test Platform

An inevitable trend has already taken shape for the application of the 5th Generation Mobile Communication Technology(5G)in the railway sector.The application scenarios and business types of the railway sector are complex and diverse,so it is indispensable to test and verify the railway 5G before actual deployment.The design and creation of the railway 5G integrated innovation test platform provides engineering design,test and verification conditions for the networking,coverage and business development of 5G public networks and 5G-R in railway scenarios.This paper introduces the design of the overall architecture for the integrated railway 5G innovation test platform according to the railway network requirements,application scenarios and intelligent development trend;respectively elaborates on the design of the 5G-R core network,bearer network and wireless access along loop tracks,in combination with the characteristics of railway scenarios and the requirements of railway dispatching,operation and safety;raises further solutions on the network deployment and coverage schemes of 5G public networks so as to meet the application requirements of 5G public networks.The study results show that the integrated railway 5G innovation test platform scheme contains co-existence of 5G public and private networks,combines the indoor and outdoor scenarios,as well as takes into account of the dynamic and static tests so as to meet the environmental requirements for the integrated railway 5G test and application of all network functions,for which it can provide comprehensive technical support for railway 5G technology research and development,standard formulation,testing,etc.

A Public Blockchain Consensus Mechanism for Fault-Tolerant Distributed Computing in LEO Satellite Communications

In LEO(Low Earth Orbit)satellite communication systems,the satellite network is made up of a large number of satellites,the dynamically changing network environment affects the results of distributed computing.In order to improve the fault tolerance rate,a novel public blockchain consensus mechanism that applies a distributed computing architecture in a public network is proposed.Redundant calculation of blockchain ensures the credibility of the results;and the transactions with calculation results of a task are stored distributed in sequence in Directed Acyclic Graphs(DAG).The transactions issued by nodes are connected to form a net.The net can quickly provide node reputation evaluation that does not rely on third parties.Simulations show that our proposed blockchain has the following advantages:1.The task processing speed of the blockchain can be close to that of the fastest node in the entire blockchain;2.When the tasks’arrival time intervals and demanded working nodes(WNs)meet certain conditions,the network can tolerate more than 50%of malicious devices;3.No matter the number of nodes in the blockchain is increased or reduced,the network can keep robustness by adjusting the task’s arrival time interval and demanded WNs.

Analysis of Call Drop Problem for Remote Access Server on Server Side

Call drop is one of the most common problems encountered by ISP with PSTN access. In this pacer several reasons on server side that cause modem disconnection are analyzed. In the last part of this paper, some solutions are Put forward to reduce call drop rate.

Architecture and Key Technology of Distributed Intelligent Open Systems

High-speed large-bandwidth networks and growth in rich internet applications has brought unprecedented pressure to bear on telecom operators. Consequently, operators need to play to the advantages of their networks, make good use of their large customer bases, and expand their business resources in service, platform, and interface. Network and customer resources should be integrated in order to create new business ecosystems. This paper describes new threats and challenges facing telecom operators and analyzes how leading operators are handling transformation in terms of operations and business model. A new concept called distributed intelligent open system （DIOS）—a public computing communication network—is proposed. The architecture and key technologies of DIOS is discussed in detail.

Predicting Stock Closing Price with Stock Network Public Opinion Based on AdaBoost-AAFSA-Elman Model and CEEMDAN Algorithm

To solve low prediction accuracy of Elman in predicting stock closing price,the model of adaptive boosting(AdaBoost)-improved artificial fish swarm algorithm(AAFSA)-Elman based on complete ensemble em-pirical mode decomposition with adaptive noise(CEEMDAN)is proposed.By adding different white noise to the original data,CEEMDAN algorithm is used to decompose attributes serial selected by Boruta algorithm and text mining.To optimize the weight and threshold of Elman,self-adaption step length and view scope are used to improve artificial fish swarm algorithm(AFSA).AdaBoost algorithm is used to compose 5 weak AAFSA-Elman predictors into a strong predictor by continuous iteration.Experiments show that the mean absolute percentage error(MAPE)of AdaBoost-AAFSA-Elman model reduces from 4.9423%to 1.2338%.This study provides an experimental method for the prediction of stock closing price based on network public opinio.

Improving access to urban parks through public transit optimization

This study establishes an evaluation and optimization framework for the public transit network based on social network analysis and a greedy algorithm,aiming to explore a quantitative approach to improving access to urban parks through public transit optimization.Social network analysis and the ArcGIS platform are used to build a public transit network model within Nanjing Old City and analyze its overall network structure characteristics.The study also focuses on a method to improve the convenience of reaching regional and citylevel parks by public transit by increasing access and connecting points accordingly.A greedy algorithm is introduced to generate an optimized solution for improving public transit accessibility to regional and city-level parks,consequently enhancing their utilization.The major findings include:(1)The greedy algorithm effectively enhances the performance of the public transit network,but its benefits gradually diminish as more stations are added.(2)Strategically adding stations enhances the performance of most public transit access points,creating efficient pathways for other stations to directly reach these access points and enter regional and city-level parks.(3)The optimized public transit network model offers guidance for the planning and layout of regional and city-level parks.The site selection for new parks should prioritize establishing connections with the“hubs”in the public transit network.The proposed optimization of the public transit network in this study is specific to a single type of urban park,but subsequent research could be conducted to extend the optimization of public transit accessibility around more urban public resources.

Complexity of Public Transport Networks

The theory of complex networks was used to classify public transport networks into public transportation route networks, public transportation transfer networks, and bus station networks. The practical significance of the network parameters was then analyzed. The public transport networks in Langfang, Jining, and Dalian were then chosen as specific research cases. The results show that the public transportation networks have the characteristics of complex networks, In addition, the urban transportation network parameters all significantly affect the accessibility, convenience, and terrorist security capability of the urban public transportation network. The results link the findings with the actual situations to explore means to solve transportation system problems.

Transport network downsizing based on optimal sub-network

Transportation networks are sized to efficiently achieve some set of service objectives.Under particular circumstances,such as the COVID-19 pandemic,the demand for transportation can significantly change,both qualitatively and quantitatively,resulting in an over-capacitated and less efficient network.In this paper,we address this issue by proposing a framework for resizing the network to efficiently cope with the new demand.The framework includes a model to determine an optimal transportation sub-network that guarantees the following:(i)the minimal access time from any node of the urban network to the new sub-network has not excessively increased compared to that of the original transportation network;(ii)the delay induced on any itinerary by the removal of nodes from the original transportation network has not excessively increased;and(iii)the number of removed nodes from the transportation network is within a preset known factor.A solution is optimal if it induces a minimal global delay.We modelled this problem as a Mixed Integer Linear Program and applied it to the public bus transportation network of Lyon,France,in a case study.In order to respond to operational issues,the framework also includes a decision tool that helps the network planners to decide which bus lines to close and which ones to leave open according to specific trade-off preferences.The results on real data in Lyon show that the optimal sub-network from the MILP model can be used to feed the decision tool,leading to operational scenarios for network planners.

Prediction of network public opinion based on bald eagle algorithm optimized radial basis function neural network

Purpose-In the new era of highly developed Internet information,the prediction of the development trend of network public opinion has a very important reference significance for monitoring and control of public opinion by relevant government departments.Design/methodology/approach-Aiming at the complex and nonlinear characteristics of the network public opinion,considering the accuracy and stability of the applicable model,a network public opinion prediction model based on the bald eagle algorithm optimized radial basis function neural network(BES-RBF)is proposed.Empirical research is conducted with Baidu indexes such as“COVID-19”,“Winter Olympic Games”,“The 100th Anniversary of the Founding of the Party”and“Aerospace”as samples of network public opinion.Findings-The experimental results show that the model proposed in this paper can better describe the development trend of different network public opinion information,has good stability in predictive performance and can provide a good decision-making reference for government public opinion control departments.Originality/value-A method for optimizing the central value,weight,width and other parameters of the radial basis function neural network with the bald eagle algorithm is given,and it is applied to network public opinion trend prediction.The example verifies that the prediction algorithm has higher accuracy and better stability.