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.

基于Faculty Opinions最新推荐评分的生物医学科技论文评价指标相关性研究

目的/意义分析不同生物医学科技论文数据库中的各类评价指标,挖掘其中隐含关联。方法/过程以Faculty Opinions推荐的文献为基础,分别从Altmetric、Scopus、WOS数据平台获取各类代表性指标,运用SPSS软件进行斯皮尔曼相关性比较分析。结果/结论不同学科类别文章Faculty Opinions最新推荐评分中,RS与WSS的相关度最高,RCR与RS相关度中等,Scopus各指标均与社会计量学各指标高度相关,Scopus与WOS各指标之间的相关度较高。

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.

Use of cognitive-behavioral career coaching to reduce work anxiety and depression in public employees

BACKGROUND Public employees worldwide are increasingly concerned about work anxiety and depression.Cognitive-behavioral career coaching has emerged as a promising strategy for addressing these mental health disorders,which can negatively impact on a person's overall well-being and performance.AIM To examine whether cognitive-behavioral career coaching reduces work anxiety and depression among Nigerian public employees.METHODS A total of 120 public employees(n=60)suffering from severe anxiety and depression were randomly assigned to the treatment or control groups in this study.Cognitive behavioral coaching was provided twice a week to those in the treatment group,whereas no treatment was given to those in the control group.As part of the study,the Hamilton Anxiety Rating Scales and Beck Depression Inventory were used to collect data.RESULTS Analysis of covariance of the data from participants indicates a significant effect of cognitive-behavioral career coaching on work anxiety and depression.CONCLUSION Insights into the underlying mechanisms by which cognitive behavior career coaching exerts its effects have been gained from this study.Also,the study has gathered valuable data that can inform future practice and guide the development of strategies for supporting mental health at work.

A Blind Batch Encryption and Public Ledger-Based Protocol for Sharing Sensitive Data

For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and allows privacy information to be preserved.Data owners can tightly manage their data with efficient revocation and only grant one-time adaptive access for the fulfillment of the requester.We prove that our protocol is semanticallly secure,blind,and secure against oblivious requesters and malicious file keepers.We also provide security analysis in the context of four typical attacks.

An Analysis of the Evolution of Online Public Opinion on Public Health Emergencies by Combining CNN-BiLSTM + Attention and LDA

In this paper, the Foxconn epidemic event in Zhengzhou was taken as an example to analyze the evolution of online public opinion on public health emergencies. In order to improve the performance of online public opinion analysis, based on the life cycle theory and LDA theory, the emotional changes of Internet users in four stages of the Foxconn incident centered on the evolution of inscription were divided. The emotions of netizen speech at different stages are analyzed based on CNN-BiLSTM + Attention model, which uses Convolutional Neural Network (CNN) to extract local features. Bi-directional Long Short-Term Memory (BiLSTM) is used to efficiently extract contextual semantic features and long distance dependencies, and then combined with attention mechanism to add emotional features. Finally, Softmax classifier realizes text emotion prediction. The experimental results show that: compared with TextCNN, BiLSTM, BiLSTM + Attenion, CNN-BiLSTM model, the emotion classification model has better effects in the accuracy rate, accuracy rate, recall rate and F value. By analyzing the emotional distribution and evolution trend of public opinion under “text topic”, the paper accurately deconstructs the development characteristics of public opinion in public health emergencies, in order to provide reference for relevant departments to deal with public opinion in public health emergencies. .

Opinion consensus incorporating higher-order interactions in individual-collective networks

In the current information society, the dissemination mechanisms and evolution laws of individual or collective opinions and their behaviors are the research hot topics in the field of opinion dynamics. First, in this paper, a two-layer network consisting of an individual-opinion layer and a collective-opinion layer is constructed, and a dissemination model of opinions incorporating higher-order interactions(i.e. OIHOI dissemination model) is proposed. Furthermore, the dynamic equations of opinion dissemination for both individuals and groups are presented. Using Lyapunov's first method,two equilibrium points, including the negative consensus point and positive consensus point, and the dynamic equations obtained for opinion dissemination, are analyzed theoretically. In addition, for individual opinions and collective opinions,some conditions for reaching negative consensus and positive consensus as well as the theoretical expression for the dissemination threshold are put forward. Numerical simulations are carried to verify the feasibility and effectiveness of the proposed theoretical results, as well as the influence of the intra-structure, inter-connections, and higher-order interactions on the dissemination and evolution of individual opinions. The main results are as follows.(i) When the intra-structure of the collective-opinion layer meets certain characteristics, then a negative or positive consensus is easier to reach for individuals.(ii) Both negative consensus and positive consensus perform best in mixed type of inter-connections in the two-layer network.(iii) Higher-order interactions can quickly eliminate differences in individual opinions, thereby enabling individuals to reach consensus faster.

Effect of distribution of fines on evolution of cooperation in spatial public goods game

In the realm of public goods game,punishment,as a potent tool,stands out for fostering cooperation.While it effectively addresses the first-order free-rider problem,the associated costs can be substantial.Punishers incur expenses in imposing sanctions,while defectors face fines.Unfortunately,these monetary elements seemingly vanish into thin air,representing a loss to the system itself.However,by virtue of the redistribution of fines to cooperators and punishers,not only can we mitigate this loss,but the rewards for these cooperative individuals can be enhanced.Based upon this premise,this paper introduces a fine distribution mechanism to the traditional pool punishment model.Under identical parameter settings,by conducting a comparative experiment with the conventional punishment model,the paper aims to investigate the impact of fine distribution on the evolution of cooperation in spatial public goods game.The experimental results clearly demonstrate that,in instances where the punishment cost is prohibitively high,the cooperative strategies of the traditional pool punishment model may completely collapse.However,the model enriched with fine distribution manages to sustain a considerable number of cooperative strategies,thus highlighting its effectiveness in promoting and preserving cooperation,even in the face of substantial punishment cost.

Opinions of Students on the Contribution of the DIVA 3D Virtual Dissection Table to the Teaching of Anatomy at the Faculty of Medicine and Odontostomatology of Bamako

Objective: Study the contribution of the DIVA 3D dissection table in the teaching of anatomy at the Faculty of Medicine and Odontology of Bamako. Material and Methods: This was a qualitative study carried out from November 1 to December 30, 2023 at the clinical and morphological anatomy laboratory of the Faculty of Medicine and Odontostomatology of Bamako. Included in this study were students who participated in practical and tutorial sessions. The variables studied during this study were: the previous performance of dissection on a cadaver by the students, the opinion of the students on dissection on a cadaver, the replacement of dissection on a cadaver by virtual dissection in the absence of a body, the level student satisfaction. Results: We surveyed 130 participants. The average age was 22 ± 0.2 years with extremes of 17 and 29 years. 95.3% of participants were students. According to 66.7% of participants, virtual dissection is a good palliative in the absence of a corpse. 95.3% of participants found using the virtual dissection table easy with an average of 7.88 ± 1.4. The overall assessment was well rated by 99.3% of participants. Conclusion: According to the results of this study, the virtual dissection table should be improved by integrating commented videos. The use of the DIVA 3D virtual dissection table during practical and tutorial sessions is well appreciated by the students. We believe that the teaching of anatomy using 3D digital technology should be included in the study programs of the Faculty of Medicine and Odontostomatology.

Discreet investors exert greater influence on cooperation in the public goods game

This paper studies the evolutionary process of cooperative behavior in a public goods game model with heterogeneous investment strategies in square lattices.In the proposed model,players are divided into defectors,cooperators and discreet investors.Among these,defectors do not participate in investing,discreet investors make heterogeneous investments based on the investment behavior and cooperation value of their neighbors,and cooperators invest equally in each neighbor.In real life,heterogeneous investment is often accompanied by time or economic costs.The discreet investors in this paper pay a certain price to obtain their neighbors'investment behavior and cooperation value,which quantifies the time and economic costs of the heterogeneous investment process.The results of Monte Carlo simulation experiments in this study show that discreet investors can effectively resist the invasion of the defectors,form a stable cooperative group and expand the cooperative advantage in evolution.However,when discreet investors pay too high a price,they lose their strategic advantage.The results in this paper help us understand the role of heterogeneous investment in promoting and maintaining human social cooperation.

Assessment of public perspectives and barriers towards dengue preventive practices using the Health Belief Model in Puducherry,India:A cross-sectional study

Objective:To assess the perspectives and barriers towards dengue preventive practices among the residents of Puducherry,India.Methods:A cross-sectional survey was conducted in 300 households in Puducherry,using a population-proportionate(7:3)distribution from urban and rural areas by grid sampling.One adult interview per household was conducted and the participants were selected using a KISH grid.A semi-structured questionnaire based on the Health Belief Model(HBM)with additional questions on knowledge assessment was used.Knowledge was assessed based on the correctness of answers and the HBM scores were calculated on a 5-point Likert scale.Participants were categorized based on the median score under each domain.Logistic regression was used for adjusted analysis and models were built to predict the performances in each domain.Results:Four percent of the participants lacked basic knowledge regarding dengue transmission.While 208(69.3%)participants did not consider themselves at risk of contracting dengue within the next year,majority perceived dengue as a disease with low severity.Around 49.3%(148)were skeptical about the benefit of time and money spent on dengue prevention.Inadequate government efforts were stated as the major barrier(47.0%)and frequent reminders(142,47.3%)as the major cue to action.Age above 50 years(aOR 1.78,95%CI 1.04-3.06,P=0.037)and rural locality(aOR 2.68,95%CI 1.52-4.71,P=0.001)were found to be significantly associated with poor knowledge scores.Urban participants had a significantly higher chance to perceive low susceptibility as compared to the rural counterparts(aOR 1.74,95%CI 1.05-2.9,P=0.03).Participants with less than a high school education had low perceived benefits(aOR 2.46,95%CI 1.52-3.96,P<0.001)and low self-efficacy scores(aOR 2.66,95%CI 1.61-4.39,P<0.001).Conclusions:This study identifies key gaps in dengue prevention,including low perceived susceptibility,mild disease perception,limited knowledge of breeding sites,and overreliance on government efforts.Tailoring interventions to community needs,stratified to factors influencing the community perspectives can significantly improve dengue prevention efforts.

Dynamic analysis of major public health emergency transmission considering the dual-layer coupling of community–resident complex networks

We construct a dual-layer coupled complex network of communities and residents to represent the interconnected risk transmission network between communities and the disease transmission network among residents. It characterizes the process of infectious disease transmission among residents between communities through the SE2IHR model considering two types of infectors. By depicting a more fine-grained social structure and combining further simulation experiments, the study validates the crucial role of various prevention and control measures implemented by communities as primary executors in controlling the epidemic. Research shows that the geographical boundaries of communities and the social interaction patterns of residents have a significant impact on the spread of the epidemic, where early detection, isolation and treatment strategies at community level are essential for controlling the spread of the epidemic. In addition, the study explores the collaborative governance model and institutional advantages of communities and residents in epidemic prevention and control.

A bibliometric analysis using machine learning to track paradigm shifts and analytical advances in forest ecology and forestry journal publications from 2010 to 2022

Forest habitats are critical for biodiversity,ecosystem services,human livelihoods,and well-being.Capacity to conduct theoretical and applied forest ecology research addressing direct(e.g.,deforestation)and indirect(e.g.,climate change)anthropogenic pressures has benefited considerably from new field-and statistical-techniques.We used machine learning and bibliometric structural topic modelling to identify 20 latent topics comprising four principal fields from a corpus of 16,952 forest ecology/forestry articles published in eight ecology and five forestry journals between 2010 and 2022.Articles published per year increased from 820 in 2010 to 2,354 in 2021,shifting toward more applied topics.Publications from China and some countries in North America and Europe dominated,with relatively fewer articles from some countries in West and Central Africa and West Asia,despite globally important forest resources.Most study sites were in some countries in North America,Central Asia,and South America,and Australia.Articles utilizing R statistical software predominated,increasing from 29.5%in 2010 to 71.4%in 2022.The most frequently used packages included lme4,vegan,nlme,MuMIn,ggplot2,car,MASS,mgcv,multcomp and raster.R was more often used in forest ecology than applied forestry articles.R software offers advantages in script and workflow-sharing compared to other statistical packages.Our findings demonstrate that the disciplines of forest ecology/forestry are expanding both in number and scope,aided by more sophisticated statistical tools,to tackle the challenges of redressing forest habitat loss and the socio-economic impacts of deforestation.

A comparative study on characteristics of retracted publications across different open access levels

Purpose:Recently,global science has shown an increasing open trend,however,the characteristics of research integrity of open access(OA)publications have rarely been studied.The aim of this study is to compare the characteristics of retracted articles across different OA levels and discover whether OA level influences the characteristics of retracted articles.Design/methodology/approach:The research conducted an analysis of 6,005 retracted publications between 2001 and 2020 from the Web of Science and Retraction Watch databases.These publications were categorized based on their OA levels,including Gold OA,Green OA,and non-OA.The study explored retraction rates,time lags and reasons within these categories.Findings:The findings of this research revealed distinct patterns in retraction rates among different OA levels.Publications with Gold OA demonstrated the highest retraction rate,followed by Green OA and non-OA.A comparison of retraction reasons between Gold OA and non-OA categories indicated similar proportions,while Green OA exhibited a higher proportion due to falsification and manipulation issues,along with a lower occurrence of plagiarism and authorship issues.The retraction time lag was shortest for Gold OA,followed by non-OA,and longest for Green OA.The prolonged retraction time for Green OA could be attributed to an atypical distribution of retraction reasons.A comparative study on characteristics of retracted publications across different open access levels Research limitations:There is no exploration of a wider range of OA levels,such as Hybrid OA and Bronze OA.Practical implications:The outcomes of this study suggest the need for increased attention to research integrity within the OA publications.The occurrences offalsification,manipulation,and ethical concerns within Green OA publications warrant attention from the scientific community.Originality/value:This study contributes to the understanding of research integrity in the realm of OA publications,shedding light on retraction patterns and reasons across different OA levels.

Data Collection and Research on the Vitality of Public Space in Traditional Villages: A Case Study of Cuandixia Village

The optimization and renewal of rural space is the foundation for building livable,business friendly and harmonious countryside.Three types of data on the spatial vitality of traditional villages are collected and analyzed.A street and alley axis map model is established using spatial syntax,and the degree of industry aggregation is quantified using POI data,and the results of syntactic calculation are validated with the help of popular review text preferences.Taking Cuandixia Village as an example,this paper found that its public space nodes have a pattern of one axis and scattered points;the street and alley space is well preserved but slightly lacking in transportation;the user group is single and the form is traditional.This paper could provide corresponding suggestions for stimulating the vitality of public spaces in traditional villages,in order to provide inspiration for the revitalization design of public spaces in traditional villages.

REDISSE in Benin and Lessons Learned for the Management of Public Health Emergencies after Five Years of Implementation

Introduction: Benin was embarked on phase 3 of the REDISSE Benin project (Regional Disease Surveillance Systems Enhancement) which began in 2018. The objectives were in five key components namely, Surveillance and health information;Laboratory capacity building;Emergency preparedness and response;Human resources management for effective disease surveillance and epidemic preparedness;and Institutional Capacity Building, Project Management, Coordination and Advocacy. After five years of implementation, this study aimed at the documentation of lessons learned and best practices. Methods: A descriptive cross-sectional study. Apart from individual semi-structured interviews, a thematic workshops bringing together the project’s main stakeholders recruited on an exhaustive way by component to identify and validate lessons learned, good practices and propose improvement mechanisms to be taken into account by the sector. Criteria were set up and used to validate best practices and lessons learned. Results: A total 54 (Surveillance workshop), 47 (Preparedness & response workshop), 53 (Human Resources workshop), 26 (Laboratories workshop) participated to the thematic workshops, and five interviews. The good practices (33: 9 for animal health, 7 for human health and 17 crosscutting) and lessons learned (10: 3 for animal health and 7 for human health) have been identified and have been the subject, depending on the case, of proposals for improvement or conditions necessary for their maintenance. Discussion: The richness of a project lies not only in the immediate achievement of its results, but also and above all, in its usefulness for similar interventions, whether in the local, regional, national or international context. It is in this context that the REDISSE project has set out to make public the various lessons learned and best practices from the implementation of its activities over a period of some five consecutive years.