International Journal of Crowd Science

Purpose Following Hovland’s persuasion theory, this paper aims to develop a conceptual model and analyzes characteristics of online political deliberation behavior from three aspects (i.e. information, situation and manager). Based on the whole interactive process of online political deliberation, this paper aims to reveal the key points that affect the response effect of the government from the persuasive perspective of online political consultation. Design/methodology/approach Based on more than 40,000 netizens’ posts and government responses from 2011 to the first half of 2019 of the Chinese political platform, this paper used the text analysis and machine learning methods to extract measurement variables of online political deliberation characteristics and the econometrics analysis method to conduct empirical research. Findings The results showed that the textual information, political environment and identity of the political objects affect the effectiveness of government response. Furthermore, for different position categories of political officials, the length of political texts, topic categories and emotional tendencies have different effects on the response effectiveness. Additionally, the effect of political time on the effectiveness of response differs. Originality/value The findings will help ascertain the characteristics of online political deliberation behavior that affect how effective government response is and provide a theoretical basis for why the public should express their political concerns.

Yuning Zhao

Xinxue Zhou

Tianmei Wang

The effect of online political deliberation on the effectiveness of government response

在线政治讨论对政府回应有效性的影响

Purpose Collaboration is a common phenomenon in human society. The best way of collaborations can make the group achieve the best interests. Because of the low cost and high repeatability of simulation, it is a good method to explore the best way of collaborations by means of simulation. The traditional simulation is difficult to adapt to the crowd intelligence network simulation, so the crowd collaborations simulation is proposed. Design/methodology/approach In this paper, the atomic swarm intelligence unit and collective swarm intelligence unit are proposed to represent the behavior of individuals and groups in physical space and the interaction between them. Findings To explore the best collaboration mode of the group, a framework of crowd collaborations simulation is proposed, which decomposes the big goal into the small goals by constructing the cooperation chain and analyzes the cooperation results and feeds them back to the next simulation. Originality/value Two kinds of swarm intelligence units are used to represent the simulated individuals in the group, and the pattern is used to represent individual behavior. It is suitable for the simulation of collaboration problems in various types and situations.

Rui Yang

Hongbo Sun

A new simulation framework for crowd collaborations

人群协作的新仿真框架

Purpose In studies related to education, sociology and economics, the relationship between students’ social relationships and their academic performance is one of the most important research topics; a large number of research studies have focused on it. This study aims to analyze the previous studies about social interaction and academic performance and attempts to reveal the underlying mechanism. Design/methodology/approach This study uses CiteSpace to analyze 1,843 articles on social relationships and academic performance from 2001 to 2019. According to the co-cited literature network results in CiteSpace, this study proposes an adapted conceptual framework of the relationship between social relationships and academic performance. This paper further examines more studies about the two most-cited articles in the co-cited literature network for better understanding. Findings From the results of the co-cited literature network, this study determines that school engagement is an important mediator between social relationships and academic performance. This paper further examines studies on school engagement and determine that, along with the self-determination theory, school engagement is influenced by multiple components of self-determination theory: autonomy, competence and relatedness. Originality/value According to the visual result in CiteSpace, this study examines a research trend in which researchers scholars start to conduct micro and detailed empirical research on the impact of the specific social networks on academic performance because of the progress of information technology. Therefore, based on the previous literature that we have analyzed, this study predicts that the trend of using information technology, such as data mining or data analysis, in this academic field will become a mainstream practice in the future.

Yin Li

Leiju Qiu

Baowen Sun

School engagement as a mediator in students’ social relationships and academic performance: a survey based on CiteSpace

学校参与在学生社会关系与学业成绩中的中介作用：基于CiteSpace的调查

Purpose The originality of the crowd cyber system lies in the fact that it possesses the intelligence of multiple groups including intelligence of people, intelligence of objects and intelligence of machines. However, quantitative analysis of the level of intelligence is not sufficient, due to many limitations, such as the unclear definition of intelligence and the inconformity of human intelligence quotient (IQ) test and artificial intelligence assessment methods. This paper aims to propose a new crowd intelligence measurement framework from the harmony of adaption and practice to measure intelligence in crowd network. Design/methodology/approach The authors draw on the ideas of traditional Confucianism, which sees intelligence from the dimensions of IQ and effectiveness. First, they clarify the related concepts of intelligence and give a new definition of crowd intelligence in the form of a set. Second, they propose four stages of the evolution of intelligence from low to high, and sort out the dilemma of intelligence measurement at the present stage. Third, they propose a framework for measuring crowd intelligence based on two dimensions. Findings The generalized IQ operator model is optimized, and a new IQ algorithm is proposed. Individuals with different IQs can have different relationships, such as cooperative, competitive, antagonistic and so on. The authors point out four representative forms of intelligence as well as its evolution stages. Research limitations/implications The authors, will use more rigorous mathematical symbols to represent the logical relationships between different individuals, and consider applying the measurement framework to a real-life situation to enrich the research on crowd intelligence in the further study. Originality/value Intelligence measurement is one of foundations of crowd science. This research lays the foundation for studying the interaction among human, machine and things from the perspective of crowd intelligence, which owns significant scientific value.

Yiqiang Feng

A measurement framework of crowd intelligence

群体智能的测量框架

Purpose Stock price prediction is a hot topic and traditional prediction methods are usually based on statistical and econometric models. However, these models are difficult to deal with nonstationary time series data. With the rapid development of the internet and the increasing popularity of social media, online news and comments often reflect investors’ emotions and attitudes toward stocks, which contains a lot of important information for predicting stock price. This paper aims to develop a stock price prediction method by taking full advantage of social media data. Design/methodology/approach This study proposes a new prediction method based on deep learning technology, which integrates traditional stock financial index variables and social media text features as inputs of the prediction model. This study uses Doc2Vec to build long text feature vectors from social media and then reduce the dimensions of the text feature vectors by stacked auto-encoder to balance the dimensions between text feature variables and stock financial index variables. Meanwhile, based on wavelet transform, the time series data of stock price is decomposed to eliminate the random noise caused by stock market fluctuation. Finally, this study uses long short-term memory model to predict the stock price. Findings The experiment results show that the method performs better than all three benchmark models in all kinds of evaluation indicators and can effectively predict stock price. Originality/value In this paper, this study proposes a new stock price prediction model that incorporates traditional financial features and social media text features which are derived from social media based on deep learning technology.

Xuan Ji

Jiachen Wang

Zhijun Yan

A stock price prediction method based on deep learning technology

基于深度学习技术的股票价格预测方法

Bo Xu

Xinpu Su

Yijun He

Index Prediction Model Based on LASSO-PCA and Deep Learning

基于LASSO-PCA和深度学习的指数预测模型

Linhao Zhang

Xudong Lu

Lizhen Cui

Deyu Zhou

Wei Guo

Optimization of Service Utility in 5G Heterogeneous Networks Using Dynamic Game

基于动态博弈的5G异构网络服务效用优化

Xiaomeng Liu

Jiarui Lin

Digital Selves Based Intelligent Construction Framework

基于数字自我的智能建造框架

Guowen Li

Wenbo Hu

Yang Zhao

Optimizing Service Efficacy in 5G HetNets: An Adaptive Acceleration PSO Approach

优化5G异构网络中的服务效能：一种自适应加速粒子群优化方法

Pengzhi Gao

Xiangwei Zheng

Tao Wang

Yuang Zhang

Graph Convolutional Neural Network Based Emotion Recognition with Brain Functional Connectivity Network

基于图卷积神经网络的脑功能连接网络情感识别

ISSN	2398-7294
h-index	15

涉及主题	计算机科学数学政治学法学心理学社会学人工智能统计社会科学机器学习社会心理学工程类操作系统经济独创性定性研究创造力人类学万维网程序设计语言哲学物理生物数据挖掘量子力学业务地理数据科学认识论知识管理计算机安全价值（数学）医学数据库历史
出版信息	出版商: Emerald Group Publishing Ltd.，出版周期: ，期刊类型: journal，开源期刊: 是
基本数据	创刊年份: 2017，原创研究文献占比: 0.00%，自引率:N.A.， Gold OA占比: 0.00%
平均审稿周期	网友分享经验：24 Weeks

International Journal of Crowd Science

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