Structured Multi-Head Attention Stock Index Prediction Method Based Adaptive Public Opinion Sentiment Vector

The present study examines the impact of short-term public opinion sentiment on the secondary market,with a focus on the potential for such sentiment to cause dramatic stock price fluctuations and increase investment risk.The quantification of investment sentiment indicators and the persistent analysis of their impact has been a complex and significant area of research.In this paper,a structured multi-head attention stock index prediction method based adaptive public opinion sentiment vector is proposed.The proposedmethod utilizes an innovative approach to transform numerous investor comments on social platforms over time into public opinion sentiment vectors expressing complex sentiments.It then analyzes the continuous impact of these vectors on the market through the use of aggregating techniques and public opinion data via a structured multi-head attention mechanism.The experimental results demonstrate that the public opinion sentiment vector can provide more comprehensive feedback on market sentiment than traditional sentiment polarity analysis.Furthermore,the multi-head attention mechanism is shown to improve prediction accuracy through attention convergence on each type of input information separately.Themean absolute percentage error(MAPE)of the proposedmethod is 0.463%,a reduction of 0.294% compared to the benchmark attention algorithm.Additionally,the market backtesting results indicate that the return was 24.560%,an improvement of 8.202% compared to the benchmark algorithm.These results suggest that themarket trading strategy based on thismethod has the potential to improve trading profits.

Evolution and spatiotemporal analysis of earthquake public opinion based on social media data

As critical conduits for the dissemination of online public opinion,social media platforms offer a timely and effective means for managing emergencies during major disasters,such as earthquakes.This study focuses on the analysis of online public opinions following the Maduo M7.4 earthquake in Qinghai Province and the Yangbi M6.4 earthquake in Yunnan Province.By collecting,cleaning,and organizing post-earthquake Sina Weibo(short for Weibo)data,we employed the Latent Dirichlet Allocation(LDA)model to extract information pertinent to public opinion on these earthquakes.This analysis included a comparison of the nature and temporal evolution of online public opinions related to both events.An emotion analysis,utilizing an emotion dictionary,categorized the emotional content of post-earthquake Weibo posts,facilitating a comparative study of the characteristics and temporal trends of online public emotions following the earthquakes.The findings were visualized using Geographic Information System(GIS)techniques.The analysis revealed certain commonalities in online public opinion following both earthquakes.Notably,the peak of online engagement occurred within the first 24 hours post-earthquake,with a rapid decline observed between 24 to 48 hours thereafter.The variation in popularity of online public opinion was linked to aftershock occurrences.Adjusted for population factors,online engagement in areas surrounding the earthquake sites and in Sichuan Province was significantly high.Initially dominated by feelings of“fear”and“surprise”,the public sentiment shifted towards a more positive outlook with the onset of rescue operations.However,distinctions in the online public response to each earthquake were also noted.Following the Yangbi earthquake,Yunnan Province reported the highest number of Weibo posts nationwide;in contrast,Qinghai Province ranked third post-Maduo earthquake,attributable to its smaller population size and extensive damage to communication infrastructure.This research offers a methodological approach for the analysis of online public opinion related to earthquakes,providing insights for the enhancement of post-disaster emergency management and public mental health support.

Research on the Evolution Structure of Fragment Disordering Public Opinion in College Students’ Network Circle Group

Clarifying the evolution structure of public opinion induced and spread by fragmentation in college students’ network circle group is the key to understanding college students’ online social psychological demands, grasping the development trend of public opinion, and designing targeted public opinion governance strategies. On the basis of identifying the key variables in the process of public opinion communication, DEMATEL-ISM model is used to explore the attribute positioning, relative importance level and hierarchical association mechanism of ante-variable and result variable, and then the governance strategies for fragment disordering public opinion in network circle groups of college students is designed. According to the study, exogenous stimuli, the uniqueness of discourse system, the number of spectacular texts and micro-narrative mode constituted the deep-rooted causes of fragment disordering public opinion. The unique situational and information attributes of network circle groups often become an important “booster” of disordered public opinion. The topic deviation is often accompanied with the formation of negative emotions. The corresponding public opinion governance strategies are sought from the aspects of shaping the network environment, adjusting the operation mechanism of the network circle group, improving the efficiency of using fragmented information, and optimizing the human resources of colleges.

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. .

新闻舆论在网络暴力治理中的功能思考——从沃尔特·李普曼的《Public Opinion》谈起

网络暴力通常以言论暴力、舆论极化的形式出现。网络暴力破坏了网络生态,并引起各国的普遍重视。由于新闻媒体议程及其报道框架影响着舆论的形成,新闻舆论对网络舆论的引导也就十分重要。当代人的“媒介化生存”产生了宏大的“拟态环境”,新闻议程对公众议程的塑造日益深重,为权威信源、新闻真相等介入网络舆论治理提供了可能性。主流媒体在场,可以消弭网络空间暴戾之气;权威新闻舆论,可以引导网络空间情感宣泄;发掘新闻真相,能够疏导网络舆论。同时,网络暴力的治理尚需多元力量的参与。

Supervision of Public Opinion under the Background of Social Co-governance-Take the Changsheng Vaccine Incident as an Example

Objective To provide reference for the news media to give play to the role of public opinion supervision in time based on the background of drug safety and social co-governance.Methods The method of case analysis was used to make a retrospective study on the Changsheng vaccine incident in 2018.Then the role of mainstream media,pharmaceutical media,and self-media in the supervision of public opinion was investigated.Results and Conclusion Both mainstream and pharmaceutical media played an excellent role in supervising the Changchun Changsheng vaccine incident.However,the content published by some pharmaceutical media was hard to understand by ordinary people.Besides,the role of self-media in public opinion supervision was polarized.Some self-media closely kept pace with mainstream media in public opinion supervision.Other self-media unilaterally pursued the click rate,publishing false information to guide wrong public opinion.The news media should optimize the supervision efficiency of drug safety.On the one hand,pharmaceutical media should pay attention to the fact that readers may not understand the difficult terms because they are not professional.On the other hand,self-media practitioners should improve their professional quality so that they will not publish some fake news to mislead 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.

COVID-19 Public Opinion and Emotion Monitoring System Based on Time Series Thermal New Word Mining

With the spread and development of new epidemics,it is of great reference value to identify the changing trends of epidemics in public emotions.We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining.A new word structure discovery scheme based on the timing explosion of network topics and a Chinese sentiment analysis method for the COVID-19 public opinion environment are proposed.Establish a“Scrapy-Redis-Bloomfilter”distributed crawler framework to collect data.The system can judge the positive and negative emotions of the reviewer based on the comments,and can also reflect the depth of the seven emotions such as Hopeful,Happy,and Depressed.Finally,we improved the sentiment discriminant model of this system and compared the sentiment discriminant error of COVID-19 related comments with the Jiagu deep learning model.The results show that our model has better generalization ability and smaller discriminant error.We designed a large data visualization screen,which can clearly show the trend of public emotions,the proportion of various emotion categories,keywords,hot topics,etc.,and fully and intuitively reflect the development of public opinion.

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.

The Indicator System Based on BP Neural Network Model for Net-mediated Public Opinion on Unexpected Emergency

Because unexpected emergency owns the characteristics of explosive,uncertain evolution direction and group diffusion,more and more researchers concentrate on and try to control it. In addition,considering the force of network,the information of the unexpected emergency will be spread and enlarged rapidly on internet. It is a new viewpoint using the indicator system to estimate the heat degree of net-mediated public opinion on unexpected emergency,which can reveal the underlying reasons about the formation of the heat degree. Moreover,we use BP(Back Propagation) neural network method instead of traditional subjective weight assignment to calculate the weights of the indicators which can make evaluation results more accurate and objective.

Social bots and mass media manipulated public opinion through dual opinion climate

Opinion dynamics models based on the multi-agent method commonly assume that interactions between individuals in a social network result in changes in their opinions.However,formation of public opinion in a social network is a macroscopic statistical result of opinions of all expressive individuals(corresponding to silent individuals).Therefore,public opinion can be manipulated not only by changing individuals'opinions,but also by changing their states of expression(or silence)which can be interpreted as the phenomenon"spiral of silence"in social psychology.Based on this theory,we establish a"dual opinion climate"model,involving social bots and mass media through a multi-agent method,to describe mechanism for manipulation of public opinion in social networks.We find that both social bots(as local variables)and mass media(as a global variable)can interfere with the formation of public opinion,cause a significant superposition effect when they act in the same direction,and inhibit each other when they act in opposite directions.

SNES: Social-Network-Oriented Public Opinion Monitoring Platform Based on ElasticSearch

With the rapid development of social network,public opinion monitoring based on social networks is becoming more and more important.Many platforms have achieved some success in public opinion monitoring.However,these platforms cannot perform well in scalability,fault tolerance,and real-time performance.In this paper,we propose a novel social-network-oriented public opinion monitoring platform based on ElasticSearch(SNES).Firstly,SNES integrates the module of distributed crawler cluster,which provides real-time social media data access.Secondly,SNES integrates ElasticSearch which can store and retrieve massive unstructured data in near real time.Finally,we design subscription module based on Apache Kafka to connect the modules of the platform together in the form of message push and consumption,improving message throughput and the ability of dynamic horizontal scaling.A great number of empirical experiments prove that the platform can adapt well to the social network with highly real-time data and has good performance in public opinion monitoring.

Public Opinion译为“舆论”考

在中国历史思想语境下,"公"以"国君"、"朝廷"为词源,与统治权力有着某种程度的重合关系,从而导致中国思想界出于反抗皇权建立民主共和国的时代精神的需要,以及西方的"public"词源为"人民",故而将public opinion翻译成为"舆论"更符合中国从传统封建帝国向现代民主国家转变的时代潮流。但与此同时,将public opinion翻译成为"舆论",导致非理性意见与多数人暴政等思想歧义。

China-Australia Relationship: Australian Public Opinion on China

The latest released Lowy Poll 2019 shows Australia’s public opinion towards China has some negative shifts again.What does this mean for yet-to-be-repaired China-Australia relationship?Does Australian public opinion have an impact on its foreign policy?This article took an analysis of this issue.We found public opinion does have an influence on Australia’s China policy formation through influencing the“popular narrative”on China issue.Nevertheless,the economic ties with China are still fundamental.In the field of foreign policy,the government has a relatively high degree of freedom for direction leading.These facts make the prospect of China-Australia relationship more dependent on the will of current government.While taking care of public opinion is always a first task for them.

South-South Coalitions, Bilateral Agreements, and Regional Coordination： Public Opinion and Brazilian Foreign Policy

Emerging powers suffer the effects from the resource deficits in attempting to project their power globally. The developing nations are faced with difficult choices in determining their resource allocation strategies when compared to the already established powers. This article uses Brazil as a case study to analyze how emerging powers articulate strategies to conduct operations across the distinct areas of the international stage, paying special attention to regional and global arenas. Our interest is to analyze how power projection strategies are articulated and formed. More specifically, our research works to understand how a country compares and relates its regional operations to its global ones.

Research on the Dissemination Mechanism and Guiding Tactics of Public Opinion in Catastrophic Event Network

This paper conducts the analysis on the dissemination mechanism and guiding tactics of public opinion in catastrophic event network. Opinion evolution mechanism can be roughly divided into two classes. One is the belief of people based on their neighbors, on the basis of the public opinion is in the social network of acquaintances. Such networks are mostly using cellular automata model for data simulation, the results of numerical simulation are speci？ c to stabilize near the critical value show that the system will reach a critical stable state. The network information collection is the source of network public opinion monitoring its breadth and depth determine the monitoring results for the clear theme of public opinion information collection. Under this basis, this paper proposes the novel idea of making the dissemination mechanism easier. The proposed idea is novel and necessary, the effectiveness is proved via the theoretical analysis.

Analysis of microblog public opinion characteristics on traditional Chinese medicine against COVID-19 based on deep learning

The opinion research on traditional Chinese medicine during the coronavirus disease 2019(COVID-19)pandemic on microblog,a social network,took into account the national people’s fight against COVID-19—the research background—the strength of traditional Chinese medicine during the pandemic—the research topic—and the public opinion—the research object.The timeline was divided into three stages according to the overall heat change.In order to explore and compare people’s emotion and topics of concern on traditional Chinese medicine during the different stages of the pandemic,deep learning analysis methods such as emotional analysis and Latent Dirichlet Allocation analysis were used.This study found that the public’s positive“emotional composition”on traditional Chinese medicine significantly improved within the timeline,while the public’s autonomy was enhanced and the overall public opinion started to show an increased trend.

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 the Current Foreign State of Interact Public Opinion

This paper analyzes the current situation of the research on Intemet public opinion from the four aspects of the dissemination and evolution of network public opinion, detection and control, audience cognitive behavior and group polarization, in order to provide a reference for the research of network public opinion in China.

Internet public opinion monitoring in public health emergencies may benefit from artificial intelligence

Internet public opinion is a summary of all kinds of emotions,attitudes and comments conveying and spreading via the internet.How to guide internet public opinion in times of public health emergencies more efficiently and more effectively has become an urgent issue to be solved.Artificial intelligence helps to monitor the internet public opinion in real time,report automatically,provide personalized guidance,make intelligent predictions and issue early warnings.Artificial intelligence technology completes its missions by building platform frameworks,innovating new types of models and simulating human subjective consciousness and behavior with the aid of big data and integration of machine learning.We believe that using Artificial intelligence technology can effectively enhance guidance,influence and credibility throughout internet.