Use Python Data Analysis to Gain Insights from Airbnb Hosts
This paper uses Python and its external data processing package to conduct an in-depth analysis machine study of Airbnb review data. Increasingly, travelers are now using Airbnb instead of staying in traditional hotels. However, in such a growing and competitive Airbnb market, many hosts may find it...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Advances in Mathematical Physics |
| Online Access: | http://dx.doi.org/10.1155/2021/1079850 |
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| _version_ | 1849413877096251392 |
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| author | Zichun Tian |
| author_facet | Zichun Tian |
| author_sort | Zichun Tian |
| collection | DOAJ |
| description | This paper uses Python and its external data processing package to conduct an in-depth analysis machine study of Airbnb review data. Increasingly, travelers are now using Airbnb instead of staying in traditional hotels. However, in such a growing and competitive Airbnb market, many hosts may find it difficult to make their listings attractive among the many. With the development of data science, the author can now analyse large amounts of data to obtain compelling evidence that helps Airbnb hosts find certain patterns in some popular properties. By learning and emulating these patterns, many hosts may be able to increase the popularity of their properties. By using Python to analyse all data from all aspects of Airbnb listings, the author proposes to test and find correlations between certain variables and popular listings. To ensure that the results are representative and general, the author used a database containing many multidimensional details and information about Airbnb listings to date. To obtain the desired results, the author uses the Pandas, NLTK, and matplotlib packages to better process and visualize the data. Finally, the author will make some recommendations to Airbnb hosts based on the evidence generated from the data in many ways. In the future, the author will build on this to further optimize the design. |
| format | Article |
| id | doaj-art-6ffc2e607f344cffad007057d2a7bc8d |
| institution | Kabale University |
| issn | 1687-9120 1687-9139 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Mathematical Physics |
| spelling | doaj-art-6ffc2e607f344cffad007057d2a7bc8d2025-08-20T03:34:00ZengWileyAdvances in Mathematical Physics1687-91201687-91392021-01-01202110.1155/2021/10798501079850Use Python Data Analysis to Gain Insights from Airbnb HostsZichun Tian0Olin Business School, Washington University in St. Louis, St. Louis 63130, USAThis paper uses Python and its external data processing package to conduct an in-depth analysis machine study of Airbnb review data. Increasingly, travelers are now using Airbnb instead of staying in traditional hotels. However, in such a growing and competitive Airbnb market, many hosts may find it difficult to make their listings attractive among the many. With the development of data science, the author can now analyse large amounts of data to obtain compelling evidence that helps Airbnb hosts find certain patterns in some popular properties. By learning and emulating these patterns, many hosts may be able to increase the popularity of their properties. By using Python to analyse all data from all aspects of Airbnb listings, the author proposes to test and find correlations between certain variables and popular listings. To ensure that the results are representative and general, the author used a database containing many multidimensional details and information about Airbnb listings to date. To obtain the desired results, the author uses the Pandas, NLTK, and matplotlib packages to better process and visualize the data. Finally, the author will make some recommendations to Airbnb hosts based on the evidence generated from the data in many ways. In the future, the author will build on this to further optimize the design.http://dx.doi.org/10.1155/2021/1079850 |
| spellingShingle | Zichun Tian Use Python Data Analysis to Gain Insights from Airbnb Hosts Advances in Mathematical Physics |
| title | Use Python Data Analysis to Gain Insights from Airbnb Hosts |
| title_full | Use Python Data Analysis to Gain Insights from Airbnb Hosts |
| title_fullStr | Use Python Data Analysis to Gain Insights from Airbnb Hosts |
| title_full_unstemmed | Use Python Data Analysis to Gain Insights from Airbnb Hosts |
| title_short | Use Python Data Analysis to Gain Insights from Airbnb Hosts |
| title_sort | use python data analysis to gain insights from airbnb hosts |
| url | http://dx.doi.org/10.1155/2021/1079850 |
| work_keys_str_mv | AT zichuntian usepythondataanalysistogaininsightsfromairbnbhosts |