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。

Withered Peach Blossoms-A Discussion for the Phenomenon of a Poor Sense of Copyright in Chinese Youth Netizens and the Suggestion Contents

This proposal expresses a standpoint concerning a discussion for the phenomenon of a poor sense of copyright in Chinese youth netizens and the suggestion.The phenomenon of a poor sense of copyright in Chinese youth netizens has disadvantages.By analyzing it,a clear status of Chinese youth netizens'problems on the poor sense of copyright will be shown.At the same time,when we consider a discussion for the phenomenon of a poor sense of copyright in Chinese youth netizens and the suggestion,we must address several main reasons that contribute to problem.These include cultural tradition restriction,incomprehensive market system,inappropriate price incentive,imperfective legal institutions and indifference education system.It is valuable for the originators feel free to create better works.Meanwhile,those factors are essential for Chinese youth netizens to consider the way to be cultivated the right spending habits.Only by analyzing all these factors together and then using these results to apply to intensity notional cultural competitiveness and form an innovative market.This paper is organized as follows:The first part will outline the poor sense of copyright in Chinese youth netizens'case studies and analyze.The second part is an introduction of the problems of the phenomenon of a poor sense of copyright in Chinese youth netizens.The reasons causing the problems are analyzed in part three.Some proposals to overcome copyright problem will be advocated in last part.This study found that enhancing copyright awareness is a very complex task for Chinese youth netizens.Cultural tradition restriction,incomprehensive market system,inappropriate price incentive,imperfective legal institutions and indifference education system are all factors which bring difficulties to promote copyright awareness in Chinese youth netizens.Combined those factors with four problems of the phenomenon in China,I offer appropriate suggestions to overcome problems and help youth netizens acquire the knowledge of copyright.

The Current Situation and Characteristics of the Great Power Mentality of China’s Netizens

The Great Power Mentality possessed by the citizens is an important part of the country’s soft power and a necessary condition for China’s rise.Based on the operational measurement of the Great Power Mentality,this paper uses the data of the 2015"Public Social Awareness Survey"as a support to examine the current status of the Chinese people's Great Power Mentality and the characteristics of the Great Power Mentality in different groups.The main research conclusions are as follows:First,the Great Power Mentality can be specifically operated into three types:self-confidence,normal mentality,and responsibility mentality;second,overall,among the three Great Power Mentality of the public,the self-confidence has the highest score(3.93),the normal mentality is second(3.32),and the responsibility mentality is the lowest(2.67);third,whether it is self-confidence,normal mentality,or responsibility mentality,the ideological position has a significant impact on people’s Great Power Mentality.The"Left"people’s Great Power Mentality scores higher.

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.

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.

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.

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.

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.

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。

一种用于方面情感四元组预测的最优意见树生成方法

使用对比学习来增强树结构表示是将树结构应用于方面级情感分析(ABSA)的主流方法,但该方法本质上依赖于数据增强,而对原始文本应用数据增强可能会删除与下游预测相关的语义信息且难以获得最优结构。为解决上述问题,提出一种用于方面情感四元组预测(ASQP)的结构熵约束的最优意见树生成方法,该方法通过文本编码器和直接生成正样本的结构编码器实现。结构编码器以意见树嵌入为输入,利用结构熵最小化原理提取意见树中固有的本质信息,并通过表示学习将该信息注入到文本表示中。在2个常见数据集上进行的实验验证了该方法的优越性。

“Opinion Leader”一词的中文翻译探析

在我国,随着博客、微博等新媒体的飞速发展,一批民间网络名人不断涌现,成为传统意义上的Opinion Leader,即"意见领袖"。但由于互联网环境下某些网络传播代表人物的不正当示范,考虑到汉语的表达习惯,"意见领袖"作为"Opinion Leader"一词的中文翻译,容易使公众产生错误联想,造成误解,甚至对我国网络舆论安全带来不容忽视的负面影响。

Two-Layer Coupled Network Model for Topic Derivation in Public Opinion Propagation

In view of the fact that news can generate derivative topics when it spreads through micro-blogs,a two-layer coupled SEIR public opinion propagation model is proposed in this paper.The model divides the process of public opinion propagation into two layers:the original topic layer and the derived topic layer.Messages are transmitted separately by the SEIR model in the two topic layers,which are independent and interactive.The influence of the topic derivation rate on the propagation trend is established by solving for the equilibrium point and propagation threshold.Further,we establish the relationship between the original topic and the derived topic by simulation.This paper uses the Baidu index to demonstrate the correctness of the model.The relationship between the derived topic and the original topic is verified by adjusting the parameters by the control variable method.The results show that the proposed model is consistent with the propagation of actual public opinion.

基于语料库的英语学习者in my opinion词块使用研究

采用语料库对比研究方法,对中国大学生使用in my opinion词块的情况进行分析。研究结果表明:(1)中国大学生在英语写作中使用in my opinion词块的频率高于英语本族语者;(2)中国大学生与英语本族语者在书面语中使用in my opinion词块存在显著差异;(3)英语专业学生与非英语专业学生对in my opinion词块的使用存在差异,非英语专业学生in my opinion词块的使用频率高于英语专业学生。文章从学习者英语词块知识的深度和广度,词块运用能力,学习者语言回避等方面分析了引起学习者过度使用in my opinion词块的原因。研究结果对大学英语教学有一定启示作用。

Simulating the Spreading of Two Competing Public Opinion Information on Complex Network

In this paper, we investigate the regularity of spreading of information and public opinions towards two competing products in complex networks. By building its mathematical model and simulating its evolution process, we have found the statistical regularity for support rates of two different products at a steady stage. The research shows that strength of the public opinion spreading is proportional to the final support rates of a product.

Ising model on evolution networks and its application on opinion formation

Many phenomena show that in a favorable circumstance an agent still has an updating possibility, and in an unfavor- able circumstance an agent also has a possibility of holding its own state and reselecting its neighbors. To describe this kind of phenomena an Ising model on evolution networks was presented and used for consensus formation and separation of opinion groups in human population. In this model the state-holding probability p and selection-rewiring probability q were introduced. The influence of this mixed dynamics of spin flips and network rewiring on the ordering behavior of the model was investigated, p hinders ordering of opinion networks and q accelerates the dynamical process of networks. Influence of q on the ordering and separating stems from its effect on average path length of networks.

A High-Performance Extraction Method for Public Opinion on Internet

Aiming at the importance of the analysis for public opinion on Internet, the authors propose a high-performance extraction method for public opinion. In this method, the space model for classification is adopted to describe the relationship between words and categories. The combined feature selection method is used to remove noisy words from the original feature space effectively. Then the category weight of words is calculated by the improved formula combining the frequency of words and distribution of words. Finally, the class weights of the not-categorized documents based on the category weight of words are obtained for realizing opinion extraction. Experiment results show that the method has comparatively high classification and good stability.

Opinion dynamics in finance and business: a literature review and research opportunities

Opinion dynamics is an opinion evolution process of a group of agents,where the final opinion distribution tends to three stable states:consensus,polarization,and fragmentation.At present,the opinion dynamics models have been extensively studied in differrent fields.This paper provides a review of opinion dynamics in finance and business,such as,finance,marketing,e-commerce,politics,and group decision making.Furthermore,identified research challenges have been proposed to promote the future research of this topic.

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.

An Approach to Evaluate the Implementation Effects of Advanced Manufacturing Technology Based on the Specialists' Opinion Selection

Since domestic corporations firstly introduced into and implemented the Advanced Manufacturing Technology (AMT),how to scientifically evaluate the implementation effects of AMT has been an urgent problem.Through the review of for- eign relative studies,this paper constructs an indicator system used to evaluate the implementation effects of AMT.Operational performance,Organizational or managerial performance,Satisfactory performance,and Competitive performance are indicators of first level in the system,and 19 indicators of second level have been selected to estimate the implementation effects of AMT.In this study,a model based on Minkowski distance discriminance to select the specialists’ opinion was designed to evaluate the indica- tor system,and the measure’s validity and practicability was proved by a case study to a diesel engine factory.

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.