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The Psychology Analysis for Post-production of College Students’ Short Video Communication Education Based on Virtual Image and Internet of Things
To improve the understanding of film and television postproduction for college students in the era of intelligent media, a study is conducted on college students’ short video communication education and audience psychology based on the rapid development of virtual image and the Internet of Things (I...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8992796/ https://www.ncbi.nlm.nih.gov/pubmed/35401327 http://dx.doi.org/10.3389/fpsyg.2022.781802 |
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author | Tang, Wufeng |
author_facet | Tang, Wufeng |
author_sort | Tang, Wufeng |
collection | PubMed |
description | To improve the understanding of film and television postproduction for college students in the era of intelligent media, a study is conducted on college students’ short video communication education and audience psychology based on the rapid development of virtual image and the Internet of Things (IoT). Primarily, the collaborative filtering algorithm (CFA) is optimized and combined with the principle of Spark and Hadoop platforms as well as the IoT and virtual image technologies. Then, a hybrid computing model is proposed, and the two algorithms are improved and combined, with 90,000 network video records as data samples. Finally, the push accuracy of the hybrid algorithm and the traditional algorithm is calculated and compared, and based on this, a questionnaire survey on the audience psychology of short video production is carried out for college students. The results show that the time user of the combined algorithm is always at least 0.4 s faster than that of a single algorithm and the running speed of the algorithm with five nodes is nearly 80% higher than the algorithm with a single node. The Spark algorithm with multinode has good versatility in image recording and processing of large groups of college students. When processing more than 100,000 image records, the deviation values of Spark and Hadoop with a single node exceeded 1.1, but the deviation value of the hybrid algorithm was still lower than 1.1. With the increase of data volume, the deviation values of the three algorithms are increasing. Compared with the traditional CFA algorithm, the optimized algorithm has a higher speed in processing data and is more accurate in content pushing. From the questionnaire survey of college students, it is found that contemporary college students are not active in learning knowledge of virtual images. Hence, it is concluded that colleges must carry out relevant courses based on short video communication education and strengthen the short video communication education of college students. A reference is provided for the development of college students’ short video communication education in the digital age. |
format | Online Article Text |
id | pubmed-8992796 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89927962022-04-09 The Psychology Analysis for Post-production of College Students’ Short Video Communication Education Based on Virtual Image and Internet of Things Tang, Wufeng Front Psychol Psychology To improve the understanding of film and television postproduction for college students in the era of intelligent media, a study is conducted on college students’ short video communication education and audience psychology based on the rapid development of virtual image and the Internet of Things (IoT). Primarily, the collaborative filtering algorithm (CFA) is optimized and combined with the principle of Spark and Hadoop platforms as well as the IoT and virtual image technologies. Then, a hybrid computing model is proposed, and the two algorithms are improved and combined, with 90,000 network video records as data samples. Finally, the push accuracy of the hybrid algorithm and the traditional algorithm is calculated and compared, and based on this, a questionnaire survey on the audience psychology of short video production is carried out for college students. The results show that the time user of the combined algorithm is always at least 0.4 s faster than that of a single algorithm and the running speed of the algorithm with five nodes is nearly 80% higher than the algorithm with a single node. The Spark algorithm with multinode has good versatility in image recording and processing of large groups of college students. When processing more than 100,000 image records, the deviation values of Spark and Hadoop with a single node exceeded 1.1, but the deviation value of the hybrid algorithm was still lower than 1.1. With the increase of data volume, the deviation values of the three algorithms are increasing. Compared with the traditional CFA algorithm, the optimized algorithm has a higher speed in processing data and is more accurate in content pushing. From the questionnaire survey of college students, it is found that contemporary college students are not active in learning knowledge of virtual images. Hence, it is concluded that colleges must carry out relevant courses based on short video communication education and strengthen the short video communication education of college students. A reference is provided for the development of college students’ short video communication education in the digital age. Frontiers Media S.A. 2022-03-25 /pmc/articles/PMC8992796/ /pubmed/35401327 http://dx.doi.org/10.3389/fpsyg.2022.781802 Text en Copyright © 2022 Tang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Tang, Wufeng The Psychology Analysis for Post-production of College Students’ Short Video Communication Education Based on Virtual Image and Internet of Things |
title | The Psychology Analysis for Post-production of College Students’ Short Video Communication Education Based on Virtual Image and Internet of Things |
title_full | The Psychology Analysis for Post-production of College Students’ Short Video Communication Education Based on Virtual Image and Internet of Things |
title_fullStr | The Psychology Analysis for Post-production of College Students’ Short Video Communication Education Based on Virtual Image and Internet of Things |
title_full_unstemmed | The Psychology Analysis for Post-production of College Students’ Short Video Communication Education Based on Virtual Image and Internet of Things |
title_short | The Psychology Analysis for Post-production of College Students’ Short Video Communication Education Based on Virtual Image and Internet of Things |
title_sort | psychology analysis for post-production of college students’ short video communication education based on virtual image and internet of things |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8992796/ https://www.ncbi.nlm.nih.gov/pubmed/35401327 http://dx.doi.org/10.3389/fpsyg.2022.781802 |
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