Keynote Speakers |
Prof. Yang Chen (H-index: 26)
Fudan University, China
Research Area:Social Computing, Computer Networks and Data Mining
Introduction:Dr. Chen Yang, Ph.D., Electronic Engineering, Tsinghua University. From September 2009 to April 2011, he was engaged in postdoctoral research at the Institute of Computer Science, University of Göttingen, Germany, and served as Deputy Director of the Computer Network Laboratory. From April 2011 to September 2014, he was engaged in postdoctoral research in the Department of Computer Science, Duke University. Since October 2014, he has been working in the School of Computer Science and Technology of Fudan University. He is currently a professor, doctoral tutor and deputy director of Shanghai Key Laboratory of Intelligent Information Processing.
Prof. Hua Wang
Zhejiang University, China
Research Area: Finance, FinTech,BlockChain,Economics
Introduction: Professor, Ph.D. (University of Tokyo), CFA, Director of Financial Innovation and FinTech Research Center.
Dr Wang has more than 10 years of professional and research experiences in international capital markets, financial products, FinTech, etc.,and 5 years as a senior Research Fellow at China Institute of Finance and Capital Markets. Dr. Wang has excellent proficiency in English and Japanese, with long-term international experience in Tokyo, London and Hong Kong, etc. He also participated in a number of research projects focusing on financial markets and government policies, and published tens of research articles and papers.
Speech Title:Brief Introduction of Solutions in Transportation to Address a Low-carbon Economy
Research Area: Public management, educational economic management, ideological and political education
Introduction: Professor Duan Xinxing, PhD supervisor, PhD in Psychology, Beijing Normal University, visiting scholar of Brigham Young University, former Dean of School of Public Administration, China University of Mining and Technology, and director of Women's Committee, China University of Mining and Technology.
Speech Title: Understanding Chinese College Students’ Emotions and Attributions during the COVID-19 Epidemic: an analysis based on Sina microblog
Abstract:The outbreak of COVID-19 resulted in various restrictive measures imposed by the Chinese government and colleges, including home quarantine and online teaching. In this context, the Internet has emerged as a crucial medium for college students to express their emotions. Measuring and evaluating emotions from online texts can provide a precise representation of the emotions of college students. To this end, this study selected 18,300 texts posted by college students on Sina microblog in 2020 and used a text-mining method to evaluate their emotions during the COVID-19 epidemic. First, an emotion attribution system was constructed using a content analysis approach combined with emotion attribution theory. The system encompasses eight dimensions: epidemic, institutional, environmental, college, interpersonal, physical and mental, input, and ability attributions. Then, a four-level Bayesian classifier was developed to evaluate and analyze the online emotions of college students along two dimensions: emotion validity and emotion attribution. The study indicated that the overall validity of college students’ emotion was negative, with low levels of arousal. As for attribution, emotion varies greatly across several attribution dimensions. In terms of emotion validity, external attributions were associated with much more positive emotions than internal attributions, although unstable attributions were associated with greater emotional arousal. The results of the study contribute to a deeper understanding of the psychological reaction mechanisms of college students during sudden public crisis events and can aid colleges and universities in improving mental health education and psychological intervention.