Vocal Minority and Silent Majority: How Do Online Ratings Reflect Population Perceptions of Quality?

Abstract

Consumer-generated ratings typically share an objective of illuminating the quality of a product or service for other buyers. While ratings have become ubiquitous and influential on the Internet, surprisingly little empirical research has investigated how these online assessments reflect the opinion of the population at large, especially in the domain of professional services where quality is often opaque to consumers. Building on the word-ofmouth literature, we examine the relationship between online ratings and population perceptions of physician quality. We leverage a unique dataset which includes direct measures of both the offline population's perception of physician quality and consumer-generated online reviews. As a result, we are able to examine how online ratings reflect patients' opinions about physician quality. In sharp contrast to the widely voiced concerns by medical practitioners, we find that physicians who are rated lower in quality by the patient population are less likely to be rated online. Although ratings provided online are positively correlated with patient population opinions, the online ratings tend to be exaggerated at the upper end of the quality spectrum. This study is the first to provide empirical evidence of the relationship between online ratings and the underlying consumer-perceived quality, and extends prior research on online word-of-mouth to the domain of professional services.

Eleições online em tempos de ‘big data’: Métodos e questões de pesquisa a partir das eleições municipais brasileiras de 2016

“…A ideia de "minoria barulhenta" (vocal minority) tem permeado discussões sobre opinião pú-blica, com especial ênfase recente (Gao, Greenwood, Agarwal, & McCullough, 2015). A questão se refere a como determinados grupos, embora minoritários, possam ser também mais atuantes, criando uma falsa percepção, perante a opinião pública, de suas grandezas e influência.…”

On the Development and Application of a Framework for Understanding the Properties and Information Quality of Online Reputation Systems

“…Examples of strategies for manipulating ratings include colluding with others to provide false ratings, paying others to provide false ratings, and using multiple accounts to provide false ratings of one's self. Despite the existence of these strategies for manipulating ratings posted using online reputation systems, Gao, Greenwood, Argarwal, and McCullough (2015) found a positive correlation between online reviews of physician quality and offline surveys completed by the population of patients. Although the results of their study suggest that physician reviews collected in online reputation systems may have fewer information quality problems than some suspect, Gao et al (2015) found a bias in these reviews with an overrepresentation of more favorable online ratings of physicians.…”

The Influence of Competition Network Structure and Competitive Behavior on Customer Performance - An Empirical Study Based on Chinese Catering Industry

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