Communications in Humanities Research ISSN: 2753-7072
Home> Volumes> Volume CHR Vol.22> Article
Research Article

The Social Cognition of Japan’s Nuclear-Contaminated Water in Chinese Social Media

Zhaoyu LaiNanchang Vocational University*

* Corresponding author: [email protected]

Abstract

The issue of nuclear-contaminated water in Japan has led to various concerns, including social public safety and food safety. This study aims to investigate the impact of this issue on the perception of social public safety among Chinese consumers by examining the spread of Japanese products in China. The study employs methodologies such as questionnaire analysis, online review collection, and examination of business statistics to analyze the data objectively. Focusing on the official discharge of nuclear-contaminated water into the sea as a crucial event, the study compares the social cognition of the audience on different social media platforms before and after the discharge. Quantitative and qualitative analysis using a subject analysis framework is used. The findings indicate that the discharge of nuclear-contaminated water in Japan has significantly improved people’s social cognition of public safety on Chinese social media, significantly changing their attitude toward Japanese products.

Keywords: boycott nuclear pollution emissions; Japanese-related product sales decline; reduce Japanese imports; condemn the Japanese government; test product safety
Published: December 7, 2023
DOI: 10.54254/2753-7064/22/20231564
Volume: CHR Vol.22
pp. 29-35
Download PDF

References

  1. Schunk, D. H. (2012). Social cognitive theory.
  2. Ricciardelli, R., Czarnuch, S., Afifi, T. O., Taillieu, T., & Carleton, R. N. (2020). Public Safety Personnel’s interpretations of potentially traumatic events. Occupational Medicine, 70(3), 155-161.
  3. Zhang, H. C., & Xu, J. (2009). Modern psychology and educational statistics.
  4. Hauke, J., & Kossowski, T. (2011). Comparison of values of Pearson’s and Spearman’s correlation coefficients on the same sets of data. Quaestiones geographicae, 30(2), 87-93.
  5. Arndt, S., Turvey, C., & Andreasen, N. C. (1999). Correlating and predicting psychiatric symptom ratings: Spearmans r versus Kendalls tau correlation. Journal of psychiatric research, 33(2), 97-104.
  6. Xu, W., Chang, C., Hung, Y. S., Kwan, S. K., & Fung, P. C. W. (2007). Order statistics correlation coefficient as a novel association measurement with applications to biosignal analysis. IEEE Transactions on Signal Processing, 55(12), 5552-5563.
  7. Liu, Y., Guo, X. Q., Li, S. W., Zhang, J. M., & Hu, Z. Z. (2022). Discharge of treated Fukushima nuclear accident contaminated water: macroscopic and microscopic simulations. National Science Review, 9(1), nwab209.
  8. Elmaslar Özbaş, E., Akın, Ö., Güneysu, S., Özcan, H. K., & Öngen, A. (2022). Changes occurring in consumption habits of people during COVID-19 pandemic and the water footprint. Environment, Development and Sustainability, 24(6), 8504-8520.
  9. Ahmad, I., Chen, W., & Chang, K. (2017). LTE-railway user priority-based cooperative resource allocation schemes for coexisting public safety and railway networks. IEEE Access, 5, 7985-8000.
  10. Ferrus, R., Sallent, O., Baldini, G., & Goratti, L. (2013). LTE: the technology driver for future public safety communications. IEEE Communications Magazine, 51(10), 154-161.