Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)

Discover Factors Which Have Effects on Airbnb’s Stakeholders by Using Python

Using Sydney Airbnb as an Example

Authors
Ziqi Wan
1Finance and Business analytics, University of Sydney, 2006 NSW, Australia
*University of Sydney’s e-mail: zwan8416@uni.sydney.edu.au
Corresponding Author
Ziqi Wan
Available Online 26 March 2022.
DOI
10.2991/aebmr.k.220307.499How to use a DOI?
Keywords
Airbnb analysis; data analysis; model building
Abstract

This report is aimed at the analysis of Sydney’s Airbnb data to provide advice to related stakeholders. Data processing, feature engineering, and model building methods were utilized to realize that endeavour.

A reliable dataset can only be formed when firstly using the data cleaning process. Linear regression, advanced non-parametric model, and model stacking are subsequently established to predict the price. According to the above analysis, insights and quantitative advice to Airbnb’s stakeholders are drawn.

Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)
Series
Advances in Economics, Business and Management Research
Publication Date
26 March 2022
ISBN
10.2991/aebmr.k.220307.499
ISSN
2352-5428
DOI
10.2991/aebmr.k.220307.499How to use a DOI?
Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Ziqi Wan
PY  - 2022
DA  - 2022/03/26
TI  - Discover Factors Which Have Effects on Airbnb’s Stakeholders by Using Python
BT  - Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)
PB  - Atlantis Press
SP  - 3058
EP  - 3062
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220307.499
DO  - 10.2991/aebmr.k.220307.499
ID  - Wan2022
ER  -