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. 2010 Nov 13:2010:202-6.

Detecting salient aspects in online reviews of health providers

Samuel Brody  1 , Noémie Elhadad
Affiliations

Detecting salient aspects in online reviews of health providers

Samuel Brody et al. AMIA Annu Symp Proc. .

Abstract

We present a fully automated method to capture what topics health consumers discuss when reviewing their health providers online. Our method does not rely on any manual tagging of the information, and operates on the text of online reviews. We analyze a large set of reviews and compare the topics discussed when reviewing providers with different specialties. This work provides a complementary view on the traditional qualitative approaches proposed so far to capturing factors for patient satisfaction. Furthermore, our research contributes to understanding in a bottom-up fashion the needs and interests of health consumers online.

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Figures

Figure 1.
Figure 1.
The important aspects inferred for each of the datasets. For each aspect, the label is in bold and was manually determined. The underlined words are the most frequent words determined by LDA for that aspect. The sentence in italics are extracted from the reviews and contains words associated with the aspect.
See this image and copyright information in PMC

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