Mining “What they talk about” for a Private Healthcare Service Provider

Lee, Angela Siew Hoong * and Lim, Tong Ming * and Chia, Mark P. C and Ea, Sue Lynn * and Yap, Mun Yee * (2017) Mining “What they talk about” for a Private Healthcare Service Provider. Archives of Business Research, 5 (5). pp. 135-156. ISSN 2054-7404

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In every industry, customer feedback contains opinions with different types of sentiment on services and products provided by companies that they purchased from. Feedback from customers help business operators to understand their customers better in order to improve different aspects of their products and services. This research studies healthcare service consumers’ perception of a private hospital on the quality of food, waiting time, services and customer expenses. This research intends to explore a set of customer’s feedbacks from year 2013 to 2016 to investigate potential new findings and to create new value added improvements to the current process. Text mining technique were used to extract and discover hidden knowledge from the unstructured feedbacks. The techniques are text parsing, filter, topic and cluster as for sentiment analysis, term frequency and weight is used in conjunction with corpus of files of text to investigate the emotional elements of the feedbacks that can be classified into either positive, neutral or negative. The outcomes of this study have highlighted several new findings and supported hypothesis of this research

Item Type: Article
Uncontrolled Keywords: Text mining; sentiment analysis; patient’s feedback; services; customer expenses; quality of food; waiting time
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Sunway University > School of Engineering and Technology [formerly School of Science and Technology until 2020] > Dept. Computing and Information Systems
Depositing User: Dr Janaki Sinnasamy
Related URLs:
Date Deposited: 09 Apr 2018 09:54
Last Modified: 07 Oct 2020 04:53

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