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基于谷歌地图评论审视顾客如何看待社区药房:多变量与情感分析。

Examining how customers perceive community pharmacies based on Google maps reviews: Multivariable and sentiment analysis.

作者信息

Laghbi Yahya Ali, Al Dhoayan Mohammed

机构信息

Department of Health Informatics, CPHHI, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.

King Abdullah International Medical Research Center, Riyadh, Saudi Arabia.

出版信息

Explor Res Clin Soc Pharm. 2024 Aug 23;15:100498. doi: 10.1016/j.rcsop.2024.100498. eCollection 2024 Sep.

DOI:10.1016/j.rcsop.2024.100498
PMID:39286030
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11403135/
Abstract

OBJECTIVE

This study aims to understand customer perceptions of community pharmacies utilizing publicly available data from Google Maps platform.

MATERIALS AND METHODS

Python was used to scrape data with Google Maps APIs. As a result, 17,237 reviews were collected from 512 pharmacies distributed over Riyadh city, Saudi Arabia. Logistic regression was conducted to test the relationships between multiple variables and the given score. In addition, sentiment analysis using VADER (Valence Aware Dictionary for Sentiment Reasoning) model was conducted on written reviews, followed by cross-tabulation and chi-square tests.

RESULTS

The Logistic regression model implies that a unit increase in the Pharmacy score enhances the odds of attaining a higher score by approximately 3.734 times. The Mann-Whitney test showed that a notable and statistically significant difference between "written reviews" and "unwritten reviews" (U = 39,928,072.5,  < 0.001). The Pearson chi-square test generated a value of 2991.315 with 8 degrees of freedom, leading to a value of 0.000.

DISCUSSION

Our study found that the willingness of reviewers to write reviews depends on their perception. This study provides a descriptive analysis of conducted sentiment analysis using VADAR. The chi-square test indicates a significant relationship between rating scores and review sentiments.

CONCLUSION

This study offers valuable findings on customer perception of community pharmacies using a new source of data.

摘要

目的

本研究旨在利用谷歌地图平台的公开数据,了解客户对社区药房的看法。

材料与方法

使用Python通过谷歌地图应用程序编程接口(APIs)来抓取数据。结果,从沙特阿拉伯利雅得市分布的512家药房收集了17237条评论。进行逻辑回归以检验多个变量与给定分数之间的关系。此外,对书面评论进行了使用VADER(情感推理的效价感知词典)模型的情感分析,随后进行了交叉表分析和卡方检验。

结果

逻辑回归模型表明,药房分数每增加一个单位,获得更高分数的几率会提高约3.734倍。曼-惠特尼检验表明,“书面评论”和“未书面评论”之间存在显著且具有统计学意义的差异(U = 39928072.5,< 0.001)。Pearson卡方检验产生了一个自由度为8的2991.315的值,导致P值为0.000。

讨论

我们的研究发现评论者撰写评论的意愿取决于他们的看法。本研究提供了对使用VADAR进行的情感分析的描述性分析。卡方检验表明评分分数与评论情感之间存在显著关系。

结论

本研究利用新的数据来源,提供了关于客户对社区药房看法的有价值的研究结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eebf/11403135/ed3d8fc7f8cc/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eebf/11403135/28744d4445ba/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eebf/11403135/acedfe5fb09c/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eebf/11403135/f9a124540aa7/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eebf/11403135/ed3d8fc7f8cc/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eebf/11403135/28744d4445ba/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eebf/11403135/acedfe5fb09c/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eebf/11403135/f9a124540aa7/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eebf/11403135/ed3d8fc7f8cc/gr4.jpg

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