What Can Online Doctor Reviews Tell Us? A Deep Learning Assisted Study of Telehealth Service

Date
2023-01-03
Authors
Hao, Haijing
Zhang, Bin
Zhan, Yongcheng
Wu, Jiang
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2130
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Abstract
The present study develops a novel deep learning method which assists text mining of online doctor reviews to extract underlying sentiment scores. Those scores can be used to estimate a healthcare service quality model to investigate how the online doctor reviews impact the online doctor consultation demand. Based on the data from the largest online health platforms in China, our model results show that the underlying sentiment scores have statistically significant impacts on the demand of online doctor consultation. Theoretically, the present study constructs an innovative deep learning algorithm with a better performance than four widely used text mining methods, which can be applied to text mining of many online forums or social media texts. Empirically, our model results show what factors impact the health service quality and online doctor consultation demand, and following those factors, healthcare professionals can improve their service.
Description
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Data Analytics, Data Mining, and Machine Learning for Social Media, deep learning, online doctor consultation service, online doctor review, sentiment score, text mining
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10
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Proceedings of the 56th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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