Design of digital economy consumer psychology prediction model based on canopy clustering algorithm
With the continuous improvement of the level of science and technology, the popularization of the Internet and the development of applications, online consumption has become a major force in personal consumption. As a result, digital consumption is born, and digital consumption is not only reflected...
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| Vydáno v: | Frontiers in psychology Ročník 13; s. 939283 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Frontiers Media S.A
02.08.2022
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| Témata: | |
| ISSN: | 1664-1078, 1664-1078 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | With the continuous improvement of the level of science and technology, the popularization of the Internet and the development of applications, online consumption has become a major force in personal consumption. As a result, digital consumption is born, and digital consumption is not only reflected in transaction consumption at the monetary level. Like some intangible services similar to the use of dating software, it can also become digital consumption. In this environment, a new economic concept, the digital economy, has emerged as the times require. The digital economy helps to achieve the rapid optimal allocation and regeneration of resources and achieve high-quality economic development. Therefore, as a new economic form, the digital economy has penetrated into all fields of human society. The Canopy algorithm is a fast clustering technique that requires only one pass through the data technology to get the results. But it is inaccurate for large-scale data clustering. Therefore, when analyzing the data, it is necessary to use the Canopy algorithm for preliminary clustering, and then combine with other algorithms or model software for refinement. This article introduces the development of the digital economy in the Internet era. It conducts a theoretical discussion on consumer psychology in the context of the digital economy. It introduces the basic calculation formula of the clustering algorithm and the algorithm flow of the Canopy clustering algorithm. It does model optimization for the Canopy clustering algorithm. On this basis, it designs questionnaires for experimental design. The indicators are divided into commodity attributes and consumer psychology. It builds a consumer psychology prediction model and tests the prediction results. The results show that the maximum difference between the prediction results of digital economy consumption psychology based on the Canopy clustering algorithm and the actual results is 0.047. It can be shown that the psychological prediction model of digital economy consumption based on the Canopy clustering algorithm has certain practicability. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Reviewed by: Guojian Lin, Fujian University of Traditional Chinese Medicine, China; Xiaotian Hao, Chongqing Technology and Business University, China This article was submitted to Organizational Psychology, a section of the journal Frontiers in Psychology Edited by: Sang-Bing Tsai, Wuyi University, China |
| ISSN: | 1664-1078 1664-1078 |
| DOI: | 10.3389/fpsyg.2022.939283 |