A Policy Category Analysis Model for Tourism Promotion in China During the COVID-19 Pandemic Based on Data Mining and Binary Regression

Chen, Tinggui; Peng, Lijuan; Yin, Xiaohua; Jing, Bailu; Yang, Jianjun; Cong, Guodong; Li, Gongfa

doi:10.2147/rmhp.s284564

Cited by 30 publications

(19 citation statements)

References 22 publications

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“…Combining Tables 10 and 13, it can be found that: (1) The emotion scores of "worktreatment", "employer", and "position" in the key themes of the position measures are positive, indicating that the public is satisfied with the treatments of newly added positions. However, the emotion score of the "enrollment" is negative and less than −1, indicating that the number of new positions is not satisfactory.…”

Section: Discussionmentioning

confidence: 99%

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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

et al. 2021

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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.

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Section: Discussionmentioning

confidence: 99%

“…The COVID-19 pandemic has plunged the global economy into panic and trouble [ 1 , 2 ]. It has caused a large-scale shutdown of work and production in the whole society, which has impacted social and economic development and the overall employment environment, and has seriously affected the employment of college graduates.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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“…There are still some deficiencies in this paper: The undiscussed issues in this paper, such as psychological change of Internet users, 32,33 the leading role of the media, 34,35 and the mood of opinion leaders, 36,37 will all affect the formation of network public opinion, but they are difficult to be quantified. Therefore, future work needs to be further integrated into the model, and studies the effect of three factors on the network public opinion formation. In the simulation analysis, the influence of relevant parameters on the formation of network public opinion is highly discussed from the macro‐level 38,39 . Consequently, the discussion on the interaction mechanism of the formation of network public opinion from the micro‐perspective is very limited 40 .…”

Section: Discussionmentioning

confidence: 99%

Modeling, simulation, and case analysis of COVID‐19 over network public opinion formation with individual internal factors and external information characteristics

Chen

Peng

Yang

et al. 2021

Concurrency and Computation

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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

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“…Inspired by it, many SR models based on convolutional neural networks have achieved powerful performance. Super‐resolution has a wide range of practical needs and application scenarios in terms of digital imaging, 14–16 video coding communication, 17–20 target recognition and capture, 21–25 and medical image analysis 26–29 . Image super‐resolution facilitates the observation of the detailed information of the image and helps the Manipulator accurately locate and grasp the object 30,31 .…”

Section: Related Workmentioning

confidence: 99%

Multiscale generative adversarial network for real‐world super‐resolution

Sun

Yang

Tao

et al. 2021

Concurrency and Computation

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Summary Recently, most deep convolutional neural networks used for image super‐resolution have achieved impressive performance on ideal datasets. However, these methods always fail in real‐world super‐resolution, and the results are blurred and structurally deformed. In this paper, a multiscale generative adversarial network (MGAN) is proposed to alleviate these issues. The model's multiscale loss function can effectively reduce the solution space and obtain the best features to reconstruct the image. The degraded framework based on kernel estimation and noise injection is mainly applied to obtain LR images that share the same domain with real‐world pictures. Moreover, the gradient branch is presented to provide other structural priors for SR processing. Simultaneously, to obtain better visual effects, LPIPS is used for perceptual losses instead of Visual Geometry Group (VGG). The competitive results show that our MGAN model outperforms the state‐of‐the‐art methods, resulting in lower noise and better visual quality, and reflects the superiority in image structure restoration.

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A Policy Category Analysis Model for Tourism Promotion in China During the COVID-19 Pandemic Based on Data Mining and Binary Regression

Cited by 30 publications

References 22 publications

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

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

Modeling, simulation, and case analysis of COVID‐19 over network public opinion formation with individual internal factors and external information characteristics

Multiscale generative adversarial network for real‐world super‐resolution

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