LTCR: Long-Text Chinese Rumor Detection Dataset (preprint)

False information can spread quickly on social media, negatively influencing the citizens' behaviors and responses to social events. To better detect all of the fake news, especially long texts which are harder to find completely, a Long-Text Chinese Rumor detection dataset named LTCR is proposed. The LTCR dataset provides a valuable resource for accurately detecting misinformation, especially in the context of complex fake news related to COVID-19. The dataset consists of 1,729 and 500 pieces of real and fake news, respectively. The average lengths of real and fake news are approximately 230 and 152 characters. We also propose \method, Salience-aware Fake News Detection Model, which achieves the highest accuracy (95.85%), fake news recall (90.91%) and F-score (90.60%) on the dataset. (https://github.com/Enderfga/DoubleCheck)

A Self-Assessment on Online Learning Efficiency by Medical Students in a Chinese Medical University during the Early Phase of the COVID-19 Outbreak (preprint)

Background At the initial stage of COVID-19 outbreak, most medical education institutions in China had to accept the sudden shift from classroom teaching to nearly 100% online instruction for different curricula. However, little has been known about medical students’ learning efficiency when learning has been completely conducted online. This study aimed at investigating medical students’ perspectives on online learning efficiency during the early phase of the COVID-19 outbreak and finding possible factors that could damage online learning efficiency.Methods Between May and July, 2020, the authors electronically distributed a self-designed questionnaire to all the 780 medical students who attended the Rural-oriented Free Tuition Medical Education program in Guangxi Medical University that locates in the southwestern China. Data on participant demographics, learning phases, academic performance, and perceptions regarding learning efficiency of online and classroom learning were collected. Wilcoxon rank sum test, Kruskal Wallis test, and polynomial Logistic regression were employed to detect differences of learning efficiency between online and classroom learning, and associations among learning phases, academic performance and online learning efficiency.Results A total of 612 medical students validly responded to this survey (valid response rate 78.46%), and they reported more positive perceptions of efficiency in the circumstance of face-to-face learning than of online learning despite of gender (P<0.001), learning phases (P<0.01), and academic performance (P<0.01). Learning phases and academic performance positively corelated with online learning efficiency (P<0.01). In responders’ opinion, the five top factors that most damaged online learning efficiency were low academic motivation, poor course design, inferiority in online teaching ability, limited interactions between faculty and students or among students, and insufficient learner engagement.Conclusion This study indicates obviously negative impact brought by pure online learning on perceived learning efficiency of medical students, and positive associations amid learning phases, academic performance, and online learning efficiency. We advise that instead of pure online instruction, more effort should be put into developing new online course design to improve learning efficiency when online instruction is conducted in large scale, and learning phase and academic performance should be taken into account for effective implementation of online learning.

Measuring of the COVID-19 Based on Time-Geography.

At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy.

The Impacts and Implications of the COVID-19 Pandemic on the Global Response to Climate Change

The coronavirus disease (COVID-19) pandemic has posed the most severe impact on the global economy and society since World War II. The pandemic has brought into focus how climate change is related with virus transmission and health, and has made the global transition toward low-carbon development more difficult and challenged the implementation of the Paris Agreement. Although the pandemic has significantly reduced carbon emissions and improved the environmental quality in the short term, it is still an unwanted event in the process of pursuing sustainable development;although objectively the pandemic has weakened countries’ efforts in terms of policies and actions to address climate change, the restructuring of global value chains in the post-COVID era has also brought new opportunities for a transition toward green and low-carbon development;although the pandemic has warned people of how important resilient governance and international cooperation is to addressing the crisis, the global climate governance process has come to a complete standstill since the outbreak of COVID-19, attenuating the mutual trust among countries and disabling the leadership in climate governance. The pandemic is a preview of the climate crisis, and it is important to learn from it for a better response. China quickly contained the pandemic within the country, actively resumed work and production, and gained a first-mover advantage in economic recovery. China should maintain strategic focus when pursuing ecological development, enhance the resilience of the socio-economic system, seize the opportunity of transitioning toward low-carbon development by turning the crisis into opportunities, and promote high-quality development within the country while fully engaging in global climate governance to seek ecological progress with other countries. [ABSTRACT FROM AUTHOR] Copyright of Chinese Journal of Urban & Environmental Studies is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)