People Thoughts Prediction Using Machine Learning on Online Shopping in Bangladesh during COVID-19 Pandemic

Sharmin Akter; Md Khairul Islam; Md Nabir Hossain; Mahfuzur Rahman; Syeda Jannatul Boshra

doi:10.1109/ICCCNT54827.2022.9984625

People Thoughts Prediction Using Machine Learning on Online Shopping in Bangladesh during COVID-19 Pandemic

Sharmin Akter^*
, Md Khairul Islam
, Md Nabir Hossain
, Mahfuzur Rahman
, Syeda Jannatul Boshra

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

E-commerce business has become a prominent entity of global retail as online transaction saves time and cost at the same time. COVID-19 pandemic and lockdown accelerated the growth of e-commerce. The new e-business companies are booming rapidly whereas insincerity in customer concern is noticeable. As a result, the purchasers are facing numerous problems while buying online. The main objective of this study is to predict preferences on online shopping of buyers and based on that analysis, the pattern can be observed. While doing the study, we used some popular Supervised machine learning algorithms such as Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Naive Bayes (NB) algorithm. Amongst those, best accuracy was delivered by the Decision Tree algorithm. The output clearly demonstrates that, people are more likely to participate in online shopping if the obstacles could be alleviate which means, buyers are still not satisfied and confident about the online platform. Hopefully, the result of this study can be a great asset for improving the E-commerce sector of Bangladesh if it is optimized wisely.

Original language	English
Title of host publication	2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665452625
DOIs	https://doi.org/10.1109/ICCCNT54827.2022.9984625
State	Published - 2022
Externally published	Yes
Event	13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022 - Kharagpur, India Duration: 3 Oct 2022 → 5 Oct 2022

Publication series

Name	2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022

Conference

Conference	13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022
Country/Territory	India
City	Kharagpur
Period	3/10/22 → 5/10/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

Decision Tree
Machine Learning
Online shopping

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Hardware and Architecture
Information Systems and Management
Safety, Risk, Reliability and Quality
Media Technology

Access to Document

10.1109/ICCCNT54827.2022.9984625

Cite this

Akter, S., Islam, M. K., Hossain, M. N., Rahman, M., & Boshra, S. J. (2022). People Thoughts Prediction Using Machine Learning on Online Shopping in Bangladesh during COVID-19 Pandemic. In 2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022 (2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCCNT54827.2022.9984625

Akter, Sharmin ; Islam, Md Khairul ; Hossain, Md Nabir et al. / People Thoughts Prediction Using Machine Learning on Online Shopping in Bangladesh during COVID-19 Pandemic. 2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022).

@inproceedings{9c824d67417e4046af5e78a35b86a6b5,

title = "People Thoughts Prediction Using Machine Learning on Online Shopping in Bangladesh during COVID-19 Pandemic",

abstract = "E-commerce business has become a prominent entity of global retail as online transaction saves time and cost at the same time. COVID-19 pandemic and lockdown accelerated the growth of e-commerce. The new e-business companies are booming rapidly whereas insincerity in customer concern is noticeable. As a result, the purchasers are facing numerous problems while buying online. The main objective of this study is to predict preferences on online shopping of buyers and based on that analysis, the pattern can be observed. While doing the study, we used some popular Supervised machine learning algorithms such as Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Naive Bayes (NB) algorithm. Amongst those, best accuracy was delivered by the Decision Tree algorithm. The output clearly demonstrates that, people are more likely to participate in online shopping if the obstacles could be alleviate which means, buyers are still not satisfied and confident about the online platform. Hopefully, the result of this study can be a great asset for improving the E-commerce sector of Bangladesh if it is optimized wisely.",

keywords = "Decision Tree, Machine Learning, Online shopping",

author = "Sharmin Akter and Islam, \{Md Khairul\} and Hossain, \{Md Nabir\} and Mahfuzur Rahman and Boshra, \{Syeda Jannatul\}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022 ; Conference date: 03-10-2022 Through 05-10-2022",

year = "2022",

doi = "10.1109/ICCCNT54827.2022.9984625",

language = "English",

series = "2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022",

address = "United States",

}

Akter, S, Islam, MK, Hossain, MN, Rahman, M & Boshra, SJ 2022, People Thoughts Prediction Using Machine Learning on Online Shopping in Bangladesh during COVID-19 Pandemic. in 2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022. 2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022, Institute of Electrical and Electronics Engineers Inc., 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022, Kharagpur, India, 3/10/22. https://doi.org/10.1109/ICCCNT54827.2022.9984625

People Thoughts Prediction Using Machine Learning on Online Shopping in Bangladesh during COVID-19 Pandemic. / Akter, Sharmin; Islam, Md Khairul; Hossain, Md Nabir et al.
2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - People Thoughts Prediction Using Machine Learning on Online Shopping in Bangladesh during COVID-19 Pandemic

AU - Akter, Sharmin

AU - Islam, Md Khairul

AU - Hossain, Md Nabir

AU - Rahman, Mahfuzur

AU - Boshra, Syeda Jannatul

PY - 2022

Y1 - 2022

N2 - E-commerce business has become a prominent entity of global retail as online transaction saves time and cost at the same time. COVID-19 pandemic and lockdown accelerated the growth of e-commerce. The new e-business companies are booming rapidly whereas insincerity in customer concern is noticeable. As a result, the purchasers are facing numerous problems while buying online. The main objective of this study is to predict preferences on online shopping of buyers and based on that analysis, the pattern can be observed. While doing the study, we used some popular Supervised machine learning algorithms such as Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Naive Bayes (NB) algorithm. Amongst those, best accuracy was delivered by the Decision Tree algorithm. The output clearly demonstrates that, people are more likely to participate in online shopping if the obstacles could be alleviate which means, buyers are still not satisfied and confident about the online platform. Hopefully, the result of this study can be a great asset for improving the E-commerce sector of Bangladesh if it is optimized wisely.

AB - E-commerce business has become a prominent entity of global retail as online transaction saves time and cost at the same time. COVID-19 pandemic and lockdown accelerated the growth of e-commerce. The new e-business companies are booming rapidly whereas insincerity in customer concern is noticeable. As a result, the purchasers are facing numerous problems while buying online. The main objective of this study is to predict preferences on online shopping of buyers and based on that analysis, the pattern can be observed. While doing the study, we used some popular Supervised machine learning algorithms such as Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Naive Bayes (NB) algorithm. Amongst those, best accuracy was delivered by the Decision Tree algorithm. The output clearly demonstrates that, people are more likely to participate in online shopping if the obstacles could be alleviate which means, buyers are still not satisfied and confident about the online platform. Hopefully, the result of this study can be a great asset for improving the E-commerce sector of Bangladesh if it is optimized wisely.

KW - Decision Tree

KW - Machine Learning

KW - Online shopping

UR - https://www.scopus.com/pages/publications/85146345879

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DO - 10.1109/ICCCNT54827.2022.9984625

M3 - Conference contribution

AN - SCOPUS:85146345879

T3 - 2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022

BT - 2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022

Y2 - 3 October 2022 through 5 October 2022

ER -

Akter S, Islam MK, Hossain MN, Rahman M, Boshra SJ. People Thoughts Prediction Using Machine Learning on Online Shopping in Bangladesh during COVID-19 Pandemic. In 2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022). doi: 10.1109/ICCCNT54827.2022.9984625

People Thoughts Prediction Using Machine Learning on Online Shopping in Bangladesh during COVID-19 Pandemic

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this