Abstract
Online reviews, i.e., evaluations of products and services posted on websites, are ubiquitous. Prior research observed substantial variance in the language of such online reviews and linked it to downstream consequences like perceived helpfulness. However, the understanding of why the language of reviews varies is limited. This is problematic because it might have vital implications for the design of IT systems and user interactions. To improve the understanding of online review language, the paper proposes that consumers’ personality, as reflected in their political ideology, is a predictor of such online review language. Specifically, it is hypothesized that reviewers’ political ideology as measured by degree of conservatism on a liberal–conservative spectrum is negatively related to review depth (the number of words and the number of arguments in a review), cognitively complex language in reviews, diversity of arguments, and positive valence in language. Support for these hypotheses is obtained through the analysis of a unique dataset that links a sample of online reviews to reviewers’ political ideology as inferred from their online news consumption recorded in clickstream data.
Highlights
Online consumer reviews are a regular feature on most consumer websites such as Amazon or Yelp and have attracted much attention in the information systems community in recent years (e.g., Li et al 2019)
We introduce political ideology to online review research because we expect several of the associated personality characteristics and motivations to predict differences in review language
We highlight that the political ideology of system users is closely related to how they engage with information technology, which has critical implications for the design of IT systems and user interactions
Summary
Online consumer reviews are a regular feature on most consumer websites such as Amazon or Yelp and have attracted much attention in the information systems community in recent years (e.g., Li et al 2019). Research has highlighted that certain properties of reviews determine their effects on review helpfulness, purchase intention, and product sales. In this regard, apart from the effects of review ratings (e.g., Chevalier and Mayzlin 2006; Clemons et al 2006), a number of studies are concerned with review language, i.e., length (e.g., Pan and Zhang 2011; Schindler and Bickart 2012), content (e.g., Willemsen et al 2011; Yin et al 2014), and linguistic style (e.g., Li et al 2019; Liu et al 2008), which are arguably at least as important for review quality and effectiveness as purely numerical ratings (Archak et al 2011; Pavlou and Dimoka 2006). Graf-Vlachy et al.: Reviews Left and Right, Bus Inf Syst Eng 63(4):403417 (2021)
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