Proceedings of the 2024 5th International Conference on Education, Knowledge and Information Management (ICEKIM 2024）

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Determinants of Sustained Social Interactions on E-commerce Shopping Guide Platforms: A Machine Learning Perspective

Authors
Kangdong Ling1, Chenxi Hu2, *
1Hefei University, Hefei, China
2Key Laboratory of Financial Big Data, Hefei University, Hefei, China
*Corresponding author. Email: hucx@hfuu.edu.cn
Corresponding Author
Chenxi Hu
Available Online 31 August 2024.
DOI
10.2991/978-94-6463-502-7_55How to use a DOI?
Keywords
E-commerce Guide Platforms; Machine Learning; social interactions; XGBoost; GPT-3
Abstract

This study investigates user behavior on e-commerce shopping guide platforms, specifically exploring the determinants of continuous social interactions. Utilizing the XGBoost algorithm, we developed a predictive model incorporating sentiment tendencies derived from user comments. By dividing a dataset of 3,212 ZHI-TECH users into training, validation, and testing subsets, the model was optimized through AutoGluon-Tabular. The optimized model was then applied to the testing dataset to predict user engagement in social interactions. With an AUC of 0.7311, Precision of 0.7028, Recall of 0.9757, and F1 score of 0.8171, the model exhibited a strong predictive performance.

Our findings provide e-commerce platforms with valuable insights into fostering user engagement, offering potential strategies to enhance user activity and satisfaction. These strategies include promoting user interaction, enhancing personal brand value, enriching community content, monitoring users’ emotional tendencies, and addressing the needs of VIP users. The study contributes significantly to the academic understanding of social interaction behaviors on e-commerce platforms.

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 5th International Conference on Education, Knowledge and Information Management (ICEKIM 2024）
Series
Atlantis Highlights in Computer Sciences
Publication Date
31 August 2024
ISBN
978-94-6463-502-7
ISSN
2589-4900
DOI
10.2991/978-94-6463-502-7_55How 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  - Kangdong Ling
AU  - Chenxi Hu
PY  - 2024
DA  - 2024/08/31
TI  - Determinants of Sustained Social Interactions on E-commerce Shopping Guide Platforms: A Machine Learning Perspective
BT  - Proceedings of the 2024 5th International Conference on Education, Knowledge and Information Management (ICEKIM 2024）
PB  - Atlantis Press
SP  - 528
EP  - 538
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-502-7_55
DO  - 10.2991/978-94-6463-502-7_55
ID  - Ling2024
ER  -