@misc{10481/80079,
year = {2023},
month = {1},
url = {https://hdl.handle.net/10481/80079},
abstract = {As doctor–patient interactive platforms, online health communities (OHCs) offer patients
massive information including doctor basic information and online patient reviews. However, how to
develop a systematic framework for doctor selection in OHCs according to doctor basic information
and online patient reviews is a challenged issue, which will be explored in this study. For doctor
basic information, we define the quantification method and aggregate them to characterize relative
influence of doctors. For online patient reviews, data analysis techniques (i.e., topics extraction and
sentiment analysis) are used to mine the core attributes and evaluations. Subsequently, frequency
weights and position weights are respectively determined by a frequency-oriented formula and
a position score-based formula, which are integrated to obtain the final importance of attributes.
Probabilistic linguistic-prospect theory-multiplicative multiobjective optimization by ratio analysis
(PL-PT-MULTIMOORA) is proposed to analyze patient satisfactions on doctors. Finally, selection
rules are made according to doctor influence and patient satisfactions so as to choose optimal and
suboptimal doctors for rational or emotional patients. The designed textual data-driven method is
successfully applied to analyze doctors from Haodf.com and some suggestions are given to help
patients pick out optimal and suboptimal doctors.},
organization = {National Natural Science Foundation of China (NSFC)	72171182	
71801175	
71871171	
72031009},
organization = {Project of Service Science and Innovation Key Laboratory of Sichuan Province	KL2105},
organization = {Project of China Scholarship Council	202107000064	
202007000143},
organization = {Andalusian government	B-TIC-590-UGR20},
organization = {FEDER/Junta de Andalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades		
P20 00673	
PID2019-103880RB-I00},
organization = {MCIN/AEI/10.13039/501100011033},
publisher = {MDPI},
keywords = {Online health communities},
keywords = {Doctor selection},
keywords = {Patient satisfactions},
keywords = {Improved MULTIMOORA},
keywords = {Selection criteria},
title = {A Textual Data-Oriented Method for Doctor Selection in Online Health Communities},
doi = {10.3390/su15021241},
author = {Du, Yinfeng and Morente Molinera, Juan Antonio and Herrera Viedma, Enrique},
}