Abstract
The traditional psychological health education for college students has some shortcomings such as specialization. As a rapidly developing information acquisition technology, big data technology has been gradually applied in various fields of society. The application of big data technology will play an important and positive role in improving and making up for the deficiency in psychological health education for college students. The purpose of this paper is to provide better psychological services for special groups of college students by studying the psychological characteristics of special groups of college students based on artificial intelligence and big data technology. In this paper, with large data and artificial intelligence technology, discusses the significance of college students’ psychological crisis intervention platform construction, objectives and the research status, combined the technology of big data, analysis the performance of the college students’ psychological crisis and the reasons, combined with the application of large data, build a platform for college students’ psychological crisis intervention, the results show that there are more than 82.1% of the students need psychological counseling. The establishment of this platform is of great theoretical and practical significance to guide college students to learn to grow by themselves.
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Acknowledgments
This work was supported by school level scientific research project of Jilin Normal University of Engineering Technology, Research on psychological problems of special college students based on positive psychological intervention strategies (No. XYB201843).
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Jia, X. (2021). Psychological Characteristics of Special Groups of College Students Based on Artificial Intelligence and Big Data Technology. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2020. Advances in Intelligent Systems and Computing, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-4572-0_120
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DOI: https://doi.org/10.1007/978-981-33-4572-0_120
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