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Prof. Dr. Tinggui Chen
Zhejiang Gongshang university

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0 Risk Management
0 Swarm Intelligence
0 system modelling
0 intelligent decsion-making

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Journal article
Published: 05 July 2021 in Healthcare
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As an important part of human resources, college graduates are the most vigorous, energetic, and creative group in society. The employment of college graduates is not only related to the vital interests of graduates themselves and the general public, but also related to the sustainable and healthy development of higher education and the country’s prosperity through science and education. However, the outbreak of COVID-19 at the end of 2019 has left China’s domestic labor and employment market in severe condition, which has a significant impact on the employment of college graduates. Based on the situation, the Chinese government has formulated a series of employment promotion policies for college graduates in accordance with local conditions to solve the current difficulties in employment of college graduates during the COVID-19Pandemic. Do these policies meet the expectations of the people? Is the policy implementation process reasonable? All these issues need to be tested and clarified urgently. This paper takes the employment promotion policy of college graduates under the COVID-19 as the research object, uses the PMC index model to screen the policy texts, obtains two perfect policy texts, and uses the Weibo comments to construct the evaluation model of policy measures support degree to analyze the social effects of employment promotion policies for college graduates. The results show that the public’s support degree with the employment promotion policies for college graduates under COVID-19 needs to be improved. Among them, the public has a neutral attitude towards position measures and transference measures but is obviously dissatisfied with subsidy measures and channel measures. Finally, suggestions for improving policy are given to make the employment policy in line with public opinion and effectively relieve the job hunting pressure of college graduates.

ACS Style

Tinggui Chen; Jingtao Rong; Lijuan Peng; Jianjun Yang; Guodong Cong; Jing Fang. Analysis of Social Effects on Employment Promotion Policies for College Graduates Based on Data Mining for Online Use Review in China during the COVID-19 Pandemic. Healthcare 2021, 9, 846 .

AMA Style

Tinggui Chen, Jingtao Rong, Lijuan Peng, Jianjun Yang, Guodong Cong, Jing Fang. Analysis of Social Effects on Employment Promotion Policies for College Graduates Based on Data Mining for Online Use Review in China during the COVID-19 Pandemic. Healthcare. 2021; 9 (7):846.

Chicago/Turabian Style

Tinggui Chen; Jingtao Rong; Lijuan Peng; Jianjun Yang; Guodong Cong; Jing Fang. 2021. "Analysis of Social Effects on Employment Promotion Policies for College Graduates Based on Data Mining for Online Use Review in China during the COVID-19 Pandemic." Healthcare 9, no. 7: 846.

Journal article
Published: 09 June 2021 in Mathematics
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With highly developed social media, English learning Applications have become a new type of mobile learning resources, and online comments posted by users after using them have not only become an important source of intellectual competition for enterprises, but can also help understand customers’ requirements, thereby improving product functionalities and service quality, and solve the pain points of product iteration and innovation. Based on this, this paper crawled the online user comments of three typical APPs (BaiCiZhan, MoMoBeiDanCi and BuBeiDanCi), through emotion analysis and hotspot mining technology, to obtain user requirements and then the K-means clustering method was used to analyze user requirements. Finally, quantile regression is used to find out which user needs have an impact on the downloads of English vocabulary APPs. The results show that: (1) Positive comments have a more significant impact on users’ downloads behavior than negative online comments. (2) English vocabulary APPs with higher downloads, both the 5-star user ratings and the increase of emotional requirement have a negative effect on the increase in APP downloads, while the enterprise’s service requirement improvement has a positive effect on the increase of APP downloads. (3) Regarding English vocabulary APPs with average or high downloads, improving the adaptability and Appearance requirements have significant negative impact on downloads. (4) The functional requirements to improve products will have a significant positive impact on the increase in downloads of English vocabulary APPs.

ACS Style

Tinggui Chen; Lijuan Peng; Jianjun Yang; Guodong Cong. Analysis of User Needs on Downloading Behavior of English Vocabulary APPs Based on Data Mining for Online Comments. Mathematics 2021, 9, 1341 .

AMA Style

Tinggui Chen, Lijuan Peng, Jianjun Yang, Guodong Cong. Analysis of User Needs on Downloading Behavior of English Vocabulary APPs Based on Data Mining for Online Comments. Mathematics. 2021; 9 (12):1341.

Chicago/Turabian Style

Tinggui Chen; Lijuan Peng; Jianjun Yang; Guodong Cong. 2021. "Analysis of User Needs on Downloading Behavior of English Vocabulary APPs Based on Data Mining for Online Comments." Mathematics 9, no. 12: 1341.

Journal article
Published: 27 May 2021 in Axioms
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With the rapid development of “We media” technology, netizens can freely express their opinions regarding enterprise products on a network platform. Consequently, online public opinion about enterprises has become a prominent issue. Negative comments posted by some netizens may trigger negative public opinion, which can have a significant impact on an enterprise’s image. From the perspective of helping enterprises deal with negative public opinion, this paper combines user portrait technology and a random forest algorithm to help enterprises identify high-risk users who have posted negative comments and thus may trigger negative public opinion. In this way, enterprises can monitor the public opinion of high-risk users to prevent negative public opinion events. Firstly, we crawled the information of users participating in discussions of product experience, and we constructed a portrait of enterprise public opinion users. Then, the characteristics of the portraits were quantified into indicators such as the user’s activity, the user’s influence, and the user’s emotional tendency, and the indicators were sorted. According to the order of the indicators, the users were divided into high-risk, moderate-risk, and low-risk categories. Next, a supervised high-risk user identification model for this classification was established, based on a random forest algorithm. In turn, the trained random forest identifier can be used to predict whether the authors of newly published public opinion information are high-risk users. Finally, a back propagation neural network algorithm was used to identify users and compared with the results of model recognition in this paper. The results showed that the average recognition accuracy of the back propagation neural network is only 72.33%, while the average recognition accuracy of the model constructed in this paper is as high as 98.49%, which verifies the feasibility and accuracy of the proposed random forest recognition method.

ACS Style

Tinggui Chen; Xiaohua Yin; Lijuan Peng; Jingtao Rong; Jianjun Yang; Guodong Cong. Monitoring and Recognizing Enterprise Public Opinion from High-Risk Users Based on User Portrait and Random Forest Algorithm. Axioms 2021, 10, 106 .

AMA Style

Tinggui Chen, Xiaohua Yin, Lijuan Peng, Jingtao Rong, Jianjun Yang, Guodong Cong. Monitoring and Recognizing Enterprise Public Opinion from High-Risk Users Based on User Portrait and Random Forest Algorithm. Axioms. 2021; 10 (2):106.

Chicago/Turabian Style

Tinggui Chen; Xiaohua Yin; Lijuan Peng; Jingtao Rong; Jianjun Yang; Guodong Cong. 2021. "Monitoring and Recognizing Enterprise Public Opinion from High-Risk Users Based on User Portrait and Random Forest Algorithm." Axioms 10, no. 2: 106.

Journal article
Published: 15 April 2021 in International Journal of Environmental Research and Public Health
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The outbreak of COVID-19 in late 2019 has had a huge impact on people’s daily life. Many restaurant businesses have been greatly affected by it. Consumers’ preferences for catering industry in China have changed, such as environmental hygiene, variety of dishes, and service methods. Therefore, the analysis of consumer preference differences and changes before and after the epidemic can not only provide emergency strategies for the catering industry but further improve the catering industry’s ability to deal with public health emergencies. This paper takes five cities in China as representatives to explore the impact of COVID-19 on China’s catering industry. Based on catering review data from August 2019 to April 2020, this paper first carries out Latent Dirichlet Allocation (LDA) topic analysis and SNOWNLP (A Python library for processing Chinese text) sentiment analysis. Then this paper compares the results of topic classification and sentiment analysis before and after the epidemic. Furthermore, differences and changes of consumer preferences are obtained and preferences of consumers under COVID-19 are analyzed and forecasted. The results of LDA thematic analysis before the outbreak of COVID-19 show that consumers tend to punch in cyber celebrity restaurants and pay more attention to the taste of dishes, whereas after it consumers pay more attention to the changes of dishes, dining environment as well as epidemic prevention. The number of packages and takeout was also increasing. However, the waiting time is constantly considered by consumers before and after COVID-19. Firstly, to our surprise, final outcome of emotional analysis showed that consumers’ emotional state was more positive after the epidemic than before. COVID-19 has changed the lifestyle of consumers, consumption concepts, and consumption habits. Therefore, businesses also need to take positive and flexible measures to actively get feedback from consumers to adjust dishes and business methods. Secondly, the psychological attitude of catering consumers is relatively positive during the epidemic period, which indicates that consumers have great confidence in the recovery and development of the catering industry. Businesses can comply with consumers’ psychology and combine consumption vouchers with restaurant discounts to promote consumers’ consumption. Finally, the environment and service play more and more important effect on consumers’ emotional scores at present, which indicates that dining state and comfortable mealtime environment are becoming increasingly valuable. Therefore, businesses need to improve service standards.

ACS Style

Chenyu Zhang; Jiayue Jiang; Hong Jin; Tinggui Chen. The Impact of COVID-19 on Consumers’ Psychological Behavior Based on Data Mining for Online User Comments in the Catering Industry in China. International Journal of Environmental Research and Public Health 2021, 18, 4178 .

AMA Style

Chenyu Zhang, Jiayue Jiang, Hong Jin, Tinggui Chen. The Impact of COVID-19 on Consumers’ Psychological Behavior Based on Data Mining for Online User Comments in the Catering Industry in China. International Journal of Environmental Research and Public Health. 2021; 18 (8):4178.

Chicago/Turabian Style

Chenyu Zhang; Jiayue Jiang; Hong Jin; Tinggui Chen. 2021. "The Impact of COVID-19 on Consumers’ Psychological Behavior Based on Data Mining for Online User Comments in the Catering Industry in China." International Journal of Environmental Research and Public Health 18, no. 8: 4178.

Journal article
Published: 07 February 2021 in Healthcare
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The wide dissemination of false information and the frequent occurrence of extreme speeches on online social platforms have become increasingly prominent, which impact on the harmony and stability of society. In order to solve the problems in the dissemination and polarization of public opinion over online social platforms, it is necessary to conduct in-depth research on the formation mechanism of the dissemination and polarization of public opinion. This article appends individual communicating willingness and forgetting effects to the Susceptible-Exposed-Infected-Recovered (SEIR) model to describe individual state transitions; secondly, it introduces three heterogeneous factors describing the characteristics of individual differences in the Jager-Amblard (J-A) model, namely: Individual conformity, individual conservative degree, and inter-individual relationship strength in order to reflect the different roles of individual heterogeneity in the opinions interaction; thirdly, it integrates the improved SEIR model and J-A model to construct the SEIR-JA model to study the formation mechanism of public opinion dissemination and polarization. Transmission parameters and polarization parameters are simulated and analyzed. Finally, a public opinion event from the pricing of China’s self-developed COVID-19 vaccine are used, and related Weibo comment data about this event are also collected so as to verify the rationality and effectiveness of the proposed model.

ACS Style

Tinggui Chen; Jingtao Rong; Jianjun Yang; Guodong Cong; Gongfa Li. Combining Public Opinion Dissemination with Polarization Process Considering Individual Heterogeneity. Healthcare 2021, 9, 176 .

AMA Style

Tinggui Chen, Jingtao Rong, Jianjun Yang, Guodong Cong, Gongfa Li. Combining Public Opinion Dissemination with Polarization Process Considering Individual Heterogeneity. Healthcare. 2021; 9 (2):176.

Chicago/Turabian Style

Tinggui Chen; Jingtao Rong; Jianjun Yang; Guodong Cong; Gongfa Li. 2021. "Combining Public Opinion Dissemination with Polarization Process Considering Individual Heterogeneity." Healthcare 9, no. 2: 176.

Research article
Published: 23 January 2021 in Concurrency and Computation: Practice and Experience
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With the development of information technology, the Internet has become an important channel of public opinion for expressing public interests, emotion, and ideas. Public emergency usually spreads via network. Due to the temporal and spatial flexibility and the information amplification of network, the opinions from different regions and background are easy to be represented as network public opinion, and have important impact on social and economic life. Thus, studying the formation mechanism of network public opinion has important theoretical and practical significance. Taking the formation process of network public opinion under emergencies as the research object, this paper first identifies the key factors influencing the formation of network public opinion, namely the internal characteristics (include individual education level, individual stubbornness, individual initial opinion, and so on) and external information of individuals (include external information intensity). Second, information intensity is introduced to describe the influence of external information feature on the formation of network public opinion. Individual education level, individual stubbornness, and individual initial opinion are analyzed to describe the influence of individual internal factors on the formation, and then its model is constructed. Through the simulation experiments, this paper analyzes the influence of external information intensity, individual education level, individual stubbornness, individual initial opinion, and other factors on the formation of network public opinion. The simulation results show that: (1) the greater intensity of public emergency reporting causes the easier formation of network public opinion; (2) the higher individual education level leads to the shorter time for completing the final formation and stable state of online public opinions, and after the formation of online public opinions, the opinion of the event is mainly neutral; (3) the greater individual's stubbornness makes the shorter formation time of online public opinion. When online public opinion reaches a stable state, the neutral opinion group dominates and firmly controls the development trend of public opinion; (4) the difference of opinions among individuals is the most important factor affecting the formation of network public opinion. Finally, the rationality and validity of the proposed model are verified by a real case. Compared with previous studies on the formation mechanism of network public opinion, this paper divides the formation process of network public opinion into three stages: individual information perception, individual decision making, and individual opinion transmission. Meanwhile, the influence of individual internal factors and external information characteristics on the formation process of network public opinion is also considered.

ACS Style

Tinggui Chen; Lijuan Peng; Jianjun Yang; Guodong Cong. Modeling, simulation, and case analysis of COVID‐19 over network public opinion formation with individual internal factors and external information characteristics. Concurrency and Computation: Practice and Experience 2021, 33, 1 .

AMA Style

Tinggui Chen, Lijuan Peng, Jianjun Yang, Guodong Cong. Modeling, simulation, and case analysis of COVID‐19 over network public opinion formation with individual internal factors and external information characteristics. Concurrency and Computation: Practice and Experience. 2021; 33 (17):1.

Chicago/Turabian Style

Tinggui Chen; Lijuan Peng; Jianjun Yang; Guodong Cong. 2021. "Modeling, simulation, and case analysis of COVID‐19 over network public opinion formation with individual internal factors and external information characteristics." Concurrency and Computation: Practice and Experience 33, no. 17: 1.

Journal article
Published: 08 January 2021 in International Journal of Environmental Research and Public Health
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With the development of Internet technology, the speed of information dissemination and accelerated updates result in frequent discussion of topics and expressions of public opinion. In general, multi-dimensional discussion topics related to the same event are often generated in the network, and the phenomenon of multi-dimensional public opinion polarization is formed under the mutual influence of groups. This paper targets the phenomenon of multi-dimensional public opinion polarization under topic-derived situations as the research object. Firstly, this paper identifies the factors influencing multi-dimensional public opinion polarization, including the mutual influence of different topic dimensions and the interaction of viewpoints within the same topic. Secondly, the topic correlation coefficient is introduced to describe the correlation among topics in different dimensions, and the individual topic support degree is used to measure the influence of topics in different dimensions and that of information from external intervention on individual attitudes. Thirdly, a multi-dimensional public opinion polarization model is constructed by further integrating multi-dimensional attitude interaction rules. Finally, the influence of individual participation, topic status, topic correlation coefficient and external intervention information on the multi-dimensional public opinion polarization process is analyzed through simulation experiments. The simulation results show that:(1) when there is a negative correlation between multi-dimensional topics, as the number of participants on different dimensional topics becomes more consistent, the conflict between multi-dimensional topics will weaken the polarization effect of overall public opinion. However, the effect of public opinion polarization will be enhanced alongwith the enhancement in the confidence of individual opinions. (2) The intervention of external intervention information in different dimensions at different times will further form a multi-dimensional and multi-stage public opinion polarization, and when the multi-dimensional topics are negatively correlated, the intervention of external intervention information will have a stronger impact on the multi-dimensional and multi-stage public opinion polarization process. Finally, the rationality and validity of the proposed model are verified by a real case.

ACS Style

Tinggui Chen; Yulong Wang; Jianjun Yang; Guodong Cong. Modeling Multidimensional Public Opinion Polarization Process under the Context of Derived Topics. International Journal of Environmental Research and Public Health 2021, 18, 472 .

AMA Style

Tinggui Chen, Yulong Wang, Jianjun Yang, Guodong Cong. Modeling Multidimensional Public Opinion Polarization Process under the Context of Derived Topics. International Journal of Environmental Research and Public Health. 2021; 18 (2):472.

Chicago/Turabian Style

Tinggui Chen; Yulong Wang; Jianjun Yang; Guodong Cong. 2021. "Modeling Multidimensional Public Opinion Polarization Process under the Context of Derived Topics." International Journal of Environmental Research and Public Health 18, no. 2: 472.

Research article
Published: 26 September 2020 in Complexity
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Currently, China is in the period of social transformation. Such transformation continuously results in high group polarization behaviors, which attracts many attentions. In order to explore the evolutionary mechanism and formation process of group polarization behavior, this paper proposes a group polarization model which is integrated into the Susceptible-Infected-Recovered-Susceptible (SIRS) epidemic model. In this paper, firstly, the SIRS epidemic model and the factors of relationship strength are introduced based on the J-A model (proposed by Jager and Amblard) to enhance the information transmission and interaction among individuals. In addition, the BA network (proposed by Barabasi and Albert) model is used as the agent adjacency model due to its closeness to the real social network structure. After that, the Monte Carlo method is applied to conduct experimental simulation. Subsequently, this paper analyzes the simulation results in threefold: (1) comparison of polarization processes with and without integration of the SIRS epidemic model; (2) adjusting the immune recovery parameter γ and the relationship strength z to explore the role of these two parameters in the polarization process; and (3) comparing the polarization effects of different network structures. Through the experiments, we find that BA network is more polarized than small-world network in the same scale. Finally, corresponding measures are proposed to prevent and mitigate the occurrence of group polarization.

ACS Style

Tinggui Chen; Jiawen Shi; Jianjun Yang; Guodong Cong; Gongfa Li. Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion Process. Complexity 2020, 2020, 1 -20.

AMA Style

Tinggui Chen, Jiawen Shi, Jianjun Yang, Guodong Cong, Gongfa Li. Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion Process. Complexity. 2020; 2020 ():1-20.

Chicago/Turabian Style

Tinggui Chen; Jiawen Shi; Jianjun Yang; Guodong Cong; Gongfa Li. 2020. "Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion Process." Complexity 2020, no. : 1-20.

Journal article
Published: 14 September 2020 in International Journal of Environmental Research and Public Health
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The occurrence of popular social events causes fluctuations and changes of public emotions, while the rapid development of online social platforms and networks has made individual interactions more intense and further escalated public emotions into public opinion. However, there is a lack of consideration of individual emotions in the current research on online public opinion. Based on this, this paper firstly expounds the quantitative representation of attitude and emotion, analyzes the formation and propagation process of online public opinion by combining individual’s expression willingness, individual’s expression ability, attitude perception value, attitude change probability and other factors, and constructs a network public opinion propagation model that takes individual emotion into consideration. Finally, the main factors affecting the formation and propagation of network public opinion are discussed through simulation experiments. The results demonstrate that: (1) fear is conducive to the formation of online public opinion, but the speed is relatively slow; sadness is not conducive to the formation, but once enough people participate in the exchange of views, the formation of online public opinion will be faster; (2) the influence of online public opinion on individual emotions expands with the increase of the number of individual interactions; (3) different network structures impact differently on the propagation of public opinion. Among them, BA (BA network is a scale-free network model proposed by Barabasi and Albert in order to explain the generation mechanism of power law, BA model has two characteristics: growth and priority connection mechanism) and ER (ER network is a network with random connectivity proposed by Erdös-Renyi) random networks can promote the propagation of online public opinion, which is prone to “one-sided” online public opinion. WS small-world networks (proposed by Watts and Strogatz. It is a kind of network with short average path length and high clustering coefficient) and fully-connected networks have an inhibitory effect on the spread of online public opinion, easily maintaining the multi-dimensional nature of online public opinion.

ACS Style

Peihua Fu; Bailu Jing; Tinggui Chen; Jianjun Yang; Guodong Cong. Modeling Network Public Opinion Propagation with the Consideration of Individual Emotions. International Journal of Environmental Research and Public Health 2020, 17, 6681 .

AMA Style

Peihua Fu, Bailu Jing, Tinggui Chen, Jianjun Yang, Guodong Cong. Modeling Network Public Opinion Propagation with the Consideration of Individual Emotions. International Journal of Environmental Research and Public Health. 2020; 17 (18):6681.

Chicago/Turabian Style

Peihua Fu; Bailu Jing; Tinggui Chen; Jianjun Yang; Guodong Cong. 2020. "Modeling Network Public Opinion Propagation with the Consideration of Individual Emotions." International Journal of Environmental Research and Public Health 17, no. 18: 6681.

Journal article
Published: 07 September 2020 in Sustainability
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During the COVID-19 pandemic, social education has shifted from face to face to online in order to avoid large gatherings and crowds for blocking the transmission of the virus. To analyze the impact of virus on user experience and deeply retrieve users’ requirements, this paper constructs a reasonable evaluation index system through obtaining user reviews about seven major online education platforms before and after the outbreak of COVID-19, and by combining the emotional analysis, hot mining technology, as well as relevant literature. At the same time, the variation coefficient method is chosen to weigh each index based on the difference of index values. Furthermore, this paper adopts the comprehensive evaluation method to analyze user experience before and after the outbreak of COVID-19, and finally finds out the change of users’ concerns regarding the online education platform. In terms of access speed, reliability, timely transmission technology of video information, course management, communication and interaction, and learning and technical support, this paper explores the supporting abilities and response levels of online education platforms during COVID-19, and puts forward corresponding measures to improve how these platforms function.

ACS Style

Tinggui Chen; Lijuan Peng; Bailu Jing; Chenyue Wu; Jianjun Yang; Guodong Cong. The Impact of the COVID-19 Pandemic on User Experience with Online Education Platforms in China. Sustainability 2020, 12, 7329 .

AMA Style

Tinggui Chen, Lijuan Peng, Bailu Jing, Chenyue Wu, Jianjun Yang, Guodong Cong. The Impact of the COVID-19 Pandemic on User Experience with Online Education Platforms in China. Sustainability. 2020; 12 (18):7329.

Chicago/Turabian Style

Tinggui Chen; Lijuan Peng; Bailu Jing; Chenyue Wu; Jianjun Yang; Guodong Cong. 2020. "The Impact of the COVID-19 Pandemic on User Experience with Online Education Platforms in China." Sustainability 12, no. 18: 7329.

Journal article
Published: 07 July 2020 in Healthcare
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The outbreak of Corona Virus Disease 2019 (COVID-19) in various countries at the end of last year has transferred traditional face-to-face teaching to online education platforms, which directly affects the quality of education. Taking user satisfaction on online education platforms in China as the research object, this paper uses a questionnaire survey and web crawler to collect experience data of online and offline users, constructs a customer satisfaction index system by analyzing emotion and the existing literature for quantitative analysis, and builds aback propagation (BP) neural network model to forecast user satisfaction. The conclusion shows that users’ personal factors have no direct influence on user satisfaction, while platform availability has the greatest influence on user satisfaction. Finally, suggestions on improving the online education platform are given to escalate the level of online education during the COVID-19 pandemic, so as to promote the reform of information-based education.

ACS Style

Tinggui Chen; Lijuan Peng; Xiaohua Yin; Jingtao Rong; Jianjun Yang; Guodong Cong. Analysis of User Satisfaction with Online Education Platforms in China during the COVID-19 Pandemic. Healthcare 2020, 8, 200 .

AMA Style

Tinggui Chen, Lijuan Peng, Xiaohua Yin, Jingtao Rong, Jianjun Yang, Guodong Cong. Analysis of User Satisfaction with Online Education Platforms in China during the COVID-19 Pandemic. Healthcare. 2020; 8 (3):200.

Chicago/Turabian Style

Tinggui Chen; Lijuan Peng; Xiaohua Yin; Jingtao Rong; Jianjun Yang; Guodong Cong. 2020. "Analysis of User Satisfaction with Online Education Platforms in China during the COVID-19 Pandemic." Healthcare 8, no. 3: 200.

Journal article
Published: 05 June 2020 in Healthcare
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With the rapid development of “we media” technology, external information about the same sudden hot social event is often involved repetitiously, leading to frequent public opinion reversal. However, the phenomenon of public opinion reversal process usually has a long-lasting duration and spreads wide, making the event itself attract the widespread attention of ordinary people. Focusing on the public opinion reversal process of sudden social hot topic (a popular and widely discussed issue), this paper firstly identifies the internal and external factors that affect the reversal, namely individual internal characteristics and external intervention information. Secondly, information intensity and the amount of information perceived by individuals are introduced to describe the impact of external intervention information on the public opinion reversal. Thirdly, the parameters of individual attention and conservation are used to describe the process of individual’s selection of external information, so as to reveal the influence of the internal characteristics on public opinion reversal, and then build a public opinion reversal model. Fourthly, the effects of information intensity and individual attention, as well as individual conservation on the process of public opinion reversal are analyzed by simulation experiment. Simulation results show that: (1) the intensity of external intervention information affects the direction and degree of public opinion reversal; (2) when individual conservation is strong or individual attention is weak, even if external intervention information is strong, there will still be no obvious reversal of public opinion. Subsequently, the rationality and effectiveness of the proposed model are verified by a real case. Finally, some recommendations and policy implications are also given.

ACS Style

Tinggui Chen; Yulong Wang; Jianjun Yang; Guodong Cong. Modeling Public Opinion Reversal Process with the Considerations of External Intervention Information and Individual Internal Characteristics. Healthcare 2020, 8, 160 .

AMA Style

Tinggui Chen, Yulong Wang, Jianjun Yang, Guodong Cong. Modeling Public Opinion Reversal Process with the Considerations of External Intervention Information and Individual Internal Characteristics. Healthcare. 2020; 8 (2):160.

Chicago/Turabian Style

Tinggui Chen; Yulong Wang; Jianjun Yang; Guodong Cong. 2020. "Modeling Public Opinion Reversal Process with the Considerations of External Intervention Information and Individual Internal Characteristics." Healthcare 8, no. 2: 160.

Journal article
Published: 11 May 2020 in Digital Communications and Networks
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The study of vehicular networks has attracted great interest in academia and the industry. In the broad area, connected vehicles and autonomous driving are technologies based on wireless data communication between vehicles or between vehicles and infrastructures. A Vehicle-to-Infrastructure (V2I) system consists of communications and computing over vehicles and related infrastructures. In such a system, wireless sensors are installed in some selected points along roads or driving areas. In autonomous driving, it is crucial for a vehicle to figure out the ideal routes by the communications between its equipped sensors and infrastructures then the vehicle is automatically moving along the routes. In this paper, we propose a Bezier curve based recursive algorithm, which effectively creates routes for vehicles through the communication between the OBU (On Board Unit) and RSUs (Road Side). In addition, this approach generates a very low overhead. We conduct simulations to test the proposed algorithm in various situations. The experiment results demonstrate that our algorithm creates almost ideal routes.

ACS Style

Jianjun Yang; Tinggui Chen; Bryson Payne; Ping Guo; Yanping Zhang; Juan Guo. Generating routes for autonomous driving in vehicle-to-infrastructure communications. Digital Communications and Networks 2020, 6, 444 -451.

AMA Style

Jianjun Yang, Tinggui Chen, Bryson Payne, Ping Guo, Yanping Zhang, Juan Guo. Generating routes for autonomous driving in vehicle-to-infrastructure communications. Digital Communications and Networks. 2020; 6 (4):444-451.

Chicago/Turabian Style

Jianjun Yang; Tinggui Chen; Bryson Payne; Ping Guo; Yanping Zhang; Juan Guo. 2020. "Generating routes for autonomous driving in vehicle-to-infrastructure communications." Digital Communications and Networks 6, no. 4: 444-451.

Research article
Published: 27 February 2020 in Concurrency and Computation: Practice and Experience
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Currently, group behaviors happen frequently with the development of network technology. As a typical social group behavior, group polarization has been attracted more and more academic attention due to its significant disturbance to public's daily lives. At present, the classic J‐A (proposed by Jager and Amblard) and D‐W (proposed by Deffuant and Weisbuch) models are used to analyze group polarization process. However, the main shortcomings existing in these models are that the individuals' psychology and their network relationships are rarely considered. In order to overcome the limitations, this article integrates the influence factors such as conformity and network relationship strength integrated into the polarization model. Besides, the BA (proposed by Barabasi and Albert) network model is used as the agent adjacency model due to its closer to the real social network structure. Subsequently, the experimental simulations are carried out with the multi‐agent Monte‐Carlo method so as to testify the efficiency and effectiveness. The results indicate that different information interaction modes have essential influence on group attitude polarization. Moreover, conformity parameters and the intensity of relationship have dual impacts on both speeding up and slowing down the polarization process.

ACS Style

Yizhou Zhang; Yibao Wang; Tinggui Chen; Jiawen Shi. Agent‐based modeling approach for group polarization behavior considering conformity and network relationship strength. Concurrency and Computation: Practice and Experience 2020, 32, 1 .

AMA Style

Yizhou Zhang, Yibao Wang, Tinggui Chen, Jiawen Shi. Agent‐based modeling approach for group polarization behavior considering conformity and network relationship strength. Concurrency and Computation: Practice and Experience. 2020; 32 (14):1.

Chicago/Turabian Style

Yizhou Zhang; Yibao Wang; Tinggui Chen; Jiawen Shi. 2020. "Agent‐based modeling approach for group polarization behavior considering conformity and network relationship strength." Concurrency and Computation: Practice and Experience 32, no. 14: 1.

Journal article
Published: 04 February 2020 in International Journal of Environmental Research and Public Health
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Social conflicts occur frequently during the social transition period and the polarization of public opinion happens occasionally. By introducing the social preference theory, the target of this paper is to reveal the micro-interaction mechanism of public opinion polarization. Firstly, we divide the social preferences of Internet users (network nodes) into three categories: egoistic, altruistic, and fair preferences, and adopt the revenue function to define the benefits obtained by individuals with different preferences among their interaction process so as to analyze their decision-making behaviors driven by the revenue. Secondly, the revenue function is used to judge the exit rules of nodes in a network, and then a dynamic network of spreading public opinion with the node (individual) exit mechanism is built based on a BA scale-free network. Subsequently, the influences of different social preferences, as well as individual revenue on the effect of public opinion polarization, are analyzed through simulation experiments. The simulation results show that (1) Different social preferences demonstrate different influences on the evolution of public opinions, (2) Individuals tend to interact with ones with different preferences, (3) The network with a single preference or a high aggregation is more likely to form public opinion polarization. Finally, the practicability and effectiveness of the proposed model are verified by a real case.

ACS Style

Tinggui Chen; Qianqian Li; Peihua Fu; Jianjun Yang; Chonghuan Xu; Guodong Cong; Gongfa Li. Public Opinion Polarization by Individual Revenue from the Social Preference Theory. International Journal of Environmental Research and Public Health 2020, 17, 946 .

AMA Style

Tinggui Chen, Qianqian Li, Peihua Fu, Jianjun Yang, Chonghuan Xu, Guodong Cong, Gongfa Li. Public Opinion Polarization by Individual Revenue from the Social Preference Theory. International Journal of Environmental Research and Public Health. 2020; 17 (3):946.

Chicago/Turabian Style

Tinggui Chen; Qianqian Li; Peihua Fu; Jianjun Yang; Chonghuan Xu; Guodong Cong; Gongfa Li. 2020. "Public Opinion Polarization by Individual Revenue from the Social Preference Theory." International Journal of Environmental Research and Public Health 17, no. 3: 946.

Research article
Published: 20 January 2020 in Complexity
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It is common that many roads in disaster areas are damaged and obstructed after sudden-onset disasters. The phenomenon often comes with escalated traffic deterioration that raises the time and cost of emergency supply scheduling. Fortunately, repairing road network will shorten the time of in-transit distribution. In this paper, according to the characteristics of emergency supplies distribution, an emergency supply scheduling model based on multiple warehouses and stricken locations is constructed to deal with the failure of part of road networks in the early postdisaster phase. The detailed process is as follows. When part of the road networks fail, we firstly determine whether to repair the damaged road networks, and then a model of reliable emergency supply scheduling based on bi-level programming is proposed. Subsequently, an improved artificial bee colony algorithm is presented to solve the problem mentioned above. Finally, through a case study, the effectiveness and efficiency of the proposed model and algorithm are verified.

ACS Style

Tinggui Chen; Shiwen Wu; Jianjun Yang; Guodong Cong; Gongfa Li. Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters. Complexity 2020, 2020, 1 -15.

AMA Style

Tinggui Chen, Shiwen Wu, Jianjun Yang, Guodong Cong, Gongfa Li. Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters. Complexity. 2020; 2020 ():1-15.

Chicago/Turabian Style

Tinggui Chen; Shiwen Wu; Jianjun Yang; Guodong Cong; Gongfa Li. 2020. "Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters." Complexity 2020, no. : 1-15.

Journal article
Published: 23 November 2019 in International Journal of Environmental Research and Public Health
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Emergency logistics plays an important role in the rescue process after sudden disasters. However, in the process of emergency logistics activities, risks may arise due to scheduling problems or insufficient supply of warehouse stocks, resulting in an insufficient rescue capacity. In addition, the risk of emergency logistics is random and may exist in a certain link or throughout the whole rescue process of emergency logistics. Consequently, the disaster site may be invaded by sudden disaster risk due to the lack of necessary material supplies. The entire emergency logistics system may be destroyed and cause even greater losses as well. Based on this phenomenon, this paper introduces reliability factors of materials and combines the complex network theory to build an emergency logistics network and analyze the emergency logistics risk propagation mechanism. This paper firstly builds an emergency logistics network based on complex network theory. Then, it combines the improved epidemic model to analyze the influencing factors of risk propagation in the emergency logistics network. Finally, this paper probes into the emergency logistics risk propagation mechanisms and processes in terms of network type, material reliability, rescue speed, etc. Furthermore, this paper identifies key factors for risk control and proposes countermeasures to further spread risks, thereby reducing the risk to loss of economic life.

ACS Style

Tinggui Chen; Shiwen Wu; Jianjun Yang; Guodong Cong. Risk Propagation Model and Its Simulation of Emergency Logistics Network Based on Material Reliability. International Journal of Environmental Research and Public Health 2019, 16, 4677 .

AMA Style

Tinggui Chen, Shiwen Wu, Jianjun Yang, Guodong Cong. Risk Propagation Model and Its Simulation of Emergency Logistics Network Based on Material Reliability. International Journal of Environmental Research and Public Health. 2019; 16 (23):4677.

Chicago/Turabian Style

Tinggui Chen; Shiwen Wu; Jianjun Yang; Guodong Cong. 2019. "Risk Propagation Model and Its Simulation of Emergency Logistics Network Based on Material Reliability." International Journal of Environmental Research and Public Health 16, no. 23: 4677.

Research article
Published: 15 November 2019 in Concurrency and Computation: Practice and Experience
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The ant colony labor division model can be used to solve the dynamic and variable traffic signal timing problem because of its adaptive and self‐adjusting characteristics. Based on the basic model, this paper proposes a new extended ant colony labor division model for traffic signal timing. This model is combined with the vehicle characteristics to modify the calculation method of environmental stimulus values. Using the vehicle delay in the unit period, the original fixed response threshold is modified to the dynamic response threshold, and the state transition equation is reconstructed. Based on the mixed traffic flow model of two‐phase single‐point intersection cellular automata, through comparative experiments and discussion and analysis, it is found that the extended ant colony labor division model can effectively improve road traffic capacity according to road conditions and reasonable traffic signal timing.

ACS Style

Changbing Jiang; Tinggui Chen; Ruolan Li; Liang Li; Gongfa Li; Chonghuan Xu; Shufang Li. Construction of extended ant colony labor division model for traffic signal timing and its application in mixed traffic flow model of single intersection. Concurrency and Computation: Practice and Experience 2019, 32, 1 .

AMA Style

Changbing Jiang, Tinggui Chen, Ruolan Li, Liang Li, Gongfa Li, Chonghuan Xu, Shufang Li. Construction of extended ant colony labor division model for traffic signal timing and its application in mixed traffic flow model of single intersection. Concurrency and Computation: Practice and Experience. 2019; 32 (7):1.

Chicago/Turabian Style

Changbing Jiang; Tinggui Chen; Ruolan Li; Liang Li; Gongfa Li; Chonghuan Xu; Shufang Li. 2019. "Construction of extended ant colony labor division model for traffic signal timing and its application in mixed traffic flow model of single intersection." Concurrency and Computation: Practice and Experience 32, no. 7: 1.

Journal article
Published: 02 October 2019 in Mathematics
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Nowadays, hot issues are likely become bipolar or multipolar after heated discussion on the Internet. This article is focused on the study of the polarization phenomenon and establishes a public opinion polarization model with the considerations of individual heterogeneity and dynamic conformity. At first, this article introduces the dynamic changing function of an individual’s conformity tendency to other’s attitudes in the interaction process. It further defines the influential weight between different interactive individuals, and expands the interactive individual from complete homogeneity to initial attitude heterogeneity, and finally, conformity heterogeneity. Then, through simulation experiments, we find that the degree of changing in individual attitude is limited. That is, it is difficult for the individuals who have one directional attitude at the initial time to change into another opposite attitude through interaction. In addition, individuals with low conformity within a certain threshold are more likely to form polarization. Finally, the rationality and effectiveness of the proposed model are verified by the typical case “Mimeng Event”.

ACS Style

Tinggui Chen; Qianqian Li; Jianjun Yang; Guodong Cong. Modeling of the Public Opinion Polarization Process with the Considerations of Individual Heterogeneity and Dynamic Conformity. Mathematics 2019, 7, 917 .

AMA Style

Tinggui Chen, Qianqian Li, Jianjun Yang, Guodong Cong. Modeling of the Public Opinion Polarization Process with the Considerations of Individual Heterogeneity and Dynamic Conformity. Mathematics. 2019; 7 (10):917.

Chicago/Turabian Style

Tinggui Chen; Qianqian Li; Jianjun Yang; Guodong Cong. 2019. "Modeling of the Public Opinion Polarization Process with the Considerations of Individual Heterogeneity and Dynamic Conformity." Mathematics 7, no. 10: 917.

Original article
Published: 02 July 2018 in International Journal of Machine Learning and Cybernetics
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Today, the public opinion synchronization on the network platform is becoming one of important issues worthy of careful study. In this paper, we take synchronization evolution phenomenon as an objective and adopt artificial bee colony (ABC) to evaluate network synchronization effects with optimization theory to find out an appropriate network structure. Firstly, we use the Kuramoto oscillators as a metaphor of the social system collective behavior. Secondly, combined with the social network characteristics obtained from the data of Sina Micro-Blog, a synchronization evolution model of Internet public opinion based on Kuramoto one is established. Subsequently, evolutionary multi-objective optimization model is set up and the ABC method is used to optimize the level of network synchronization, the synchronization starting time and the cost of public opinion synchronization. Finally, case analysis on “Double Eleven” Internet Marketing as well as Cadmium Poisoned Rice Event demonstrates that the synchronization performance of weak coupled system can be enhanced by offering reasonable configuration of the connection cost and the synchronization duration cost. In addition, a certain degree of increase in input cost can promote the synchronization performance and extend the synchronization duration significantly.

ACS Style

RenBin Xiao; Jin Li; Tinggui Chen. Modeling and intelligent optimization of social collective behavior with online public opinion synchronization. International Journal of Machine Learning and Cybernetics 2018, 10, 1979 -1996.

AMA Style

RenBin Xiao, Jin Li, Tinggui Chen. Modeling and intelligent optimization of social collective behavior with online public opinion synchronization. International Journal of Machine Learning and Cybernetics. 2018; 10 (8):1979-1996.

Chicago/Turabian Style

RenBin Xiao; Jin Li; Tinggui Chen. 2018. "Modeling and intelligent optimization of social collective behavior with online public opinion synchronization." International Journal of Machine Learning and Cybernetics 10, no. 8: 1979-1996.