Network Public Opinion Research Articles

A systematic literature review of crisis management in online public opinion: evolutionary path and implications for China

PurposeThis study aims to explore the dissemination and evolutionary path of online public opinion from a crisis management perspective. By clarifying the influencing factors and dynamic mechanisms of online public opinion dissemination, this study provides insights into attenuating the negative impact of online public opinion and creating a favorable ecological space for online public opinion.Design/methodology/approachThis research employs bibliometric analysis and CiteSpace software to analyze 302 Chinese articles published from 2006 to 2023 in the China National Knowledge Infrastructure (CNKI) database and 276 English articles published from 1994 to 2023 in the Web of Science core set database. Through literature keyword clustering, co-citation analysis and burst terms analysis, this paper summarizes the core scientific research institutions, scholars, hot topics and evolutionary paths of online public opinion crisis management research from both Chinese and international academic communities.FindingsThe results show that the study of online public opinion crisis management in China and internationally is centered on the life cycle theory, which integrates knowledge from information, computer and system sciences. Although there are differences in political interaction and stage evolution, the overall evolutionary path is similar, and it develops dynamically in the “benign conflict” between the expansion of the research perspective and the gradual refinement of research granularity.Originality/valueThis study summarizes the research results of online public opinion crisis management from China and the international academic community and identifies current research hotspots and theoretical evolution paths. Future research can focus on deepening the basic theories of public opinion crisis management under the influence of frontier technologies, exploring the subjectivity and emotionality of web users using fine algorithms and promoting the international development of network public opinion crisis management theory through transnational comparison and international cooperation.

Research on the Sentiment Analysis and Evolutionary Mechanism of Sudden Network Public Opinion Based on SNA-ARIMA Model with Text Mining

This article is based on the massive text data in the digital era, using text mining methods to explore the evolution mechanism of online public opinion, in order to achieve the control of public opinion trends in sudden network events and regulate the stability of online and offline public opinion. We introduced time series for decision-making assistance, combined with time series autoregressive integrated moving average model (ARIMA) for prediction, and comprehensively evaluates the evolution of public opinion from two dimensions: sentimental orientation and social network analysis (SNA). Based on this, a new exploration model for public opinion evolution, SNA-ARIMA, is constructed. The research results indicate that the process of public opinion dissemination exhibits distinct phased characteristics, and each stage is comprehensively influenced by different key nodes or factors. This study provides decision support for managing public opinion crises, making the identification of key nodes in online public opinion events, the evolution mechanism of public opinion, and the guidance of public opinion crises more systematic, forward-looking, and scientific.

Research on the Influence of Network Culture Group on College Students' Ideological and Political Education from the Perspective of Big Data Analysis

Today's society has entered the era of big data. Big data technology has been applied to ideological and political education in colleges and universities. The application of big data analysis in the field of ideological and political education in colleges and universities can promote the inclusive expansion, individualized teaching and expansion of ideological and political education in colleges and universities. Internet new media provides unprecedented space and potential for cultural innovation in the youth circle, and expands the path of production, dissemination, consumption and participation of cultural individuals and groups. The network culture circle group has gradually emerged and developed into the main place for the breeding and spread of network public opinion, which has an important impact on the ideological and political education of college students. From the perspective of big data analysis, colleges and universities need to do a good job in reshaping educational concepts, improving political positions, enhancing public opinion monitoring, and strengthening position management, and explore the path of ideological and political education for college students from the perspective of network cultural circles, so as to do a good job in ideological and political education for college students.

Enhancing Zero-Shot Stance Detection with Contrastive and Prompt Learning.

In social networks, the occurrence of unexpected events rapidly catalyzes the widespread dissemination and further evolution of network public opinion. The advent of zero-shot stance detection aligns more closely with the characteristics of stance detection in today's digital age, where the absence of training examples for specific models poses significant challenges. This task necessitates models with robust generalization abilities to discern target-related, transferable stance features within training data. Recent advances in prompt-based learning have showcased notable efficacy in few-shot text classification. Such methods typically employ a uniform prompt pattern across all instances, yet they overlook the intricate relationship between prompts and instances, thereby failing to sufficiently direct the model towards learning task-relevant knowledge and information. This paper argues for the critical need to dynamically enhance the relevance between specific instances and prompts. Thus, we introduce a stance detection model underpinned by a gated multilayer perceptron (gMLP) and a prompt learning strategy, which is tailored for zero-shot stance detection scenarios. Specifically, the gMLP is utilized to capture semantic features of instances, coupled with a control gate mechanism to modulate the influence of the gate on prompt tokens based on the semantic context of each instance, thereby dynamically reinforcing the instance-prompt connection. Moreover, we integrate contrastive learning to empower the model with more discriminative feature representations. Experimental evaluations on the VAST and SEM16 benchmark datasets substantiate our method's effectiveness, yielding a 1.3% improvement over the JointCL model on the VAST dataset.

Evaluating the effect of Chinese universities’ public opinion governance strategies through online user comments on the Weibo platform

PurposeThis study argues that online user comments on social media platforms provide feedback and evaluation functions. These functions can provide services for the relevant departments of organizations or institutions to formulate corresponding public opinion response strategies.Design/methodology/approachThis study considers Chinese universities’ public opinion events on the Weibo platform as the research object. It collects online comments on Chinese universities’ network public opinion governance strategy texts on Weibo, constructs the sentiment index based on sentiment analysis and evaluates the effectiveness of the network public opinion governance strategy adopted by university officials.FindingsThis study found the following: First, a complete information release process can effectively improve the effect of public opinion governance strategies. Second, the effect of network public opinion governance strategies was significantly influenced by the type of public opinion event. Finally, the effect of public opinion governance strategies is closely related to the severity of punishment for the subjects involved.Research limitations/implicationsThe theoretical contribution of this study lies in the application of image repair theory and strategies in the field of network public opinion governance, which further broadens the scope of the application of image repair theory and strategies.Originality/valueThis study expands online user comment research to network public opinion governance and provides a quantitative method for evaluating the effect of governance strategies.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2022-0269

Research on Risk Early Warning of Police-involved Network Public Opinion Under the Background of the Integration of "Feeling, Pointing, and Acting"

Research on Risk Early Warning of Police-involved Network Public Opinion Under the Background of the Integration of "Feeling, Pointing, and Acting"

Spillover Effect of Network Public Opinion on Market Prices of Small-Scale Agricultural Products

Network public opinion plays a crucial role in the behavior and decision making of various stakeholders, including farmers, middlemen, and consumers. It also affects the price fluctuations of small-scale agricultural products. Understanding the transmission path and spillover effect of network public opinion on the price fluctuations of these products is essential for ensuring their sustainable development and price stability. This paper selects the monthly data of network public opinion and related market prices of small-scale agricultural products from January 2014 to December 2021, constructs a network public opinion value through the sentiment classification results of deep learning models, and uses the trivariate VAR-BEKK-GARCH(1,1) model and spillover index model to study the spillover effect and spillover index of network public opinion on the market prices of small-scale agricultural products (national average price and origin price). The results show that: (1) There is a bidirectional volatility spillover effect between public opinion sentiment and the market prices of small-scale agricultural products. Additionally, this two-way volatility spillover effect is also evident between the average market prices and the origin prices of these commodities. (2) The influence of network public opinion on the market prices of small-scale agricultural products is substantial, with the spillover index being more pronounced for origin prices than for national average prices and reaching its zenith earlier. Consequently, based on these results, recommendations are provided to adapt planting and inventory strategies, enhance vigilance towards price risk transmission amongst small-scale agricultural product markets, and improve the comprehensive information platform encompassing the entire industry chain.

Retracted: Analysis of Dynamic Influence Mechanism of Network Public Opinion Based on Simulation Feature Extraction

Retracted: Analysis of Dynamic Influence Mechanism of Network Public Opinion Based on Simulation Feature Extraction

Transforming College Students' Ideological and Political Education Through Distributed Technology in the Digital Age of Network Public Opinion

Transforming College Students' Ideological and Political Education Through Distributed Technology in the Digital Age of Network Public Opinion

The formation pattern, causes, and governance of network public opinion on university emergencies.

University emergencies, garnering significant public attention and shaping network opinions, pose a crucial challenge to universities' management and societal stability. Hence, network public opinion on university emergencies is a vital issue. Nevertheless, the underlying mechanism has not been fully explored and cannot be efficiently controlled. This study aimed to explore the formation pattern of network public opinion on university emergencies, analyze its causes, and provide scientific governance strategies for coping with this issue. Based on a sample set of 204 cases from the Zhiwei Data Sharing Platform, this study classifies network public opinion on university emergencies into six types and visually analyzes their characteristics: time distribution, subject, duration, and emotion. By integrating the theory of the network public opinion field, this study develops a network public opinion field model of university emergencies to reveal its formation pattern. Furthermore, it analyzes the causes of network public opinion on university emergencies from the perspective of the public opinion lifecycle and proposes corresponding governance strategies. The sample consisted of 304 cases of real-life public opinion, and the visualization results show that public opinion on mental health and teacher-student safety constitutes the predominant types, accounting for 83.3%. High-occurrence subjects are public universities (88.24%) and students (48%). The most frequent months are July and December. 90.20% of the public opinions have a lifespan of less than 19 days, with an impact index ranging from 40 to 80. The public's emotional response to different types of public opinion varies, with negative emotions dominating. This study provides novel insights for understanding their formation and dissemination. It also provides practical implications for relevant departments to govern network public opinion on university emergencies.

Stochastic Evolutionary Game Model of Hot Topics Propagation for Network Public Opinion

Due to the rapid propagation and significant impact, the network public opinion of hot topics has become a concern of the social public and governments. The existing models based on the evolutionary game cannot reflect the real-world propagation of hot topics under uncertain environmental interference. And few researchers analyze the early intervention timing of the government on hot topics based on stochastic evolutionary game theory. To solve these problems, the government intervention parameters of punishment intensity, intervention delay, and intervention probability are introduced to build a three-party stochastic evolutionary game model of “media-netizen-government” in the multi-agent system under the scene of hot topics propagation. Then, the stochastic differential equation is expanded and simulated by the explicit forward Euler numerical method. Finally, simulation experiments are conducted to quantitatively analyze the random evolutionary process and the government intervention timing by adjusting key parameters, which can provide the optimal timing and suggestions for governments to intervene in hot topics propagation.

Research on Network Public Opinion in War Damage Incident of Major Water Conservancy Projects

Research on Network Public Opinion in War Damage Incident of Major Water Conservancy Projects

Innovation of guiding mechanism of ideological and political education in colleges and universities under the background of network public opinion

Innovation of guiding mechanism of ideological and political education in colleges and universities under the background of network public opinion

A Method for Tracing Big Data of Network Public Opinion Based on Data Mining Algorithms

A Method for Tracing Big Data of Network Public Opinion Based on Data Mining Algorithms

Study of the early warning model for network public opinion risks based on the interest preferences of internet users

Study of the early warning model for network public opinion risks based on the interest preferences of internet users

An evolution trend evaluation of social media network public opinion based on unsupervised learning

An evolution trend evaluation of social media network public opinion based on unsupervised learning

Interactive Trap: The Network Public Opinion Trial in the Carnival Scene of the Microblog Platform

Interactive Trap: The Network Public Opinion Trial in the Carnival Scene of the Microblog Platform

A method for tracing big data of network public opinion based on data mining algorithms

A method for tracing big data of network public opinion based on data mining algorithms

Research on the Governance Strategy of Network Public Opinion in the Self Media Environment

Research on the Governance Strategy of Network Public Opinion in the Self Media Environment

Classification and topic tracking of college students’ cybersecurity education based on the internet

Campus security issues have always been a hot topic of concern from all walks of life. To analyze the changes in network public opinion of college students’ campus security incidents, this study proposes to classify campus security incidents and track related topics. The classification algorithm and topic tracking algorithm for campus security incidents based on Internet technology are studied, and a prototype system of campus security incidents based on Internet is designed for analysis. The research results show that the Internet-based campus security incident prototype system can classify campus security incidents more accurately, and can also track security incidents on related topics, which provide support for student security management to a certain extent. This technology will be applied to the tracking and classification of college safety accidents, and provide certain reference for ensuring college students’ campus safety.