Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2024)

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Research on the Prediction of Overall Monthly Active Users of WeChat Mini Programs Based on Linear Regression

Authors
Lidong Liu1, Jiajia Hu1, Yantao He1, *, Sijia Liu2, Shuhua Li1, Yongbin Luo1, Rong Zhang1, Ziyu Chen1
1Department of Computer Science, Guangdong University of Science and Technology, No. 2, Songshan Lake Section, Guangzhou, 523083, China
2School of Mechanical Engineering, Hunan University of Science and Technology, Taoyuan Road, Xiangtan, 411201, China
*Corresponding author. Email: heyantao@gdust.edu.cn
Corresponding Author
Yantao He
Available Online 31 August 2024.
DOI
10.2991/978-94-6463-490-7_31How to use a DOI?
Keywords
WeChat Mini Programs market; linear regression; number of users
Abstract

In recent years, the user base of WeChat mini programs has experienced a consistent growth. This study employs a linear regression approach to forecast the future monthly active user count for these mini programs. Throughout our research, we utilized two distinct methods to independently determine the slope, thereby mitigating potential discrepancies in results. Our analysis, based on the derived linear regression model, indicates a projected upward trend in the overall monthly active user count for future mini programs. Such insights offer robust decision support for both developers and marketers, fostering the swift advancement and widespread adoption of WeChat mini programs.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2024)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
31 August 2024
ISBN
978-94-6463-490-7
ISSN
2589-4919
DOI
10.2991/978-94-6463-490-7_31How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Lidong Liu
AU  - Jiajia Hu
AU  - Yantao He
AU  - Sijia Liu
AU  - Shuhua Li
AU  - Yongbin Luo
AU  - Rong Zhang
AU  - Ziyu Chen
PY  - 2024
DA  - 2024/08/31
TI  - Research on the Prediction of Overall Monthly Active Users of WeChat Mini Programs Based on Linear Regression
BT  - Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2024)
PB  - Atlantis Press
SP  - 293
EP  - 298
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-490-7_31
DO  - 10.2991/978-94-6463-490-7_31
ID  - Liu2024
ER  -