Measurement of Trustworthiness of the Online Reviews

TL;DR

This paper proposes a formal method to quantify the trustworthiness of online reviews by analyzing reviewer rationality patterns, aiming to reduce misinformation and identify manipulative reviews in e-commerce.

Contribution

It introduces a rationality pattern function to measure reviewer trustworthiness, enhancing the detection of biased or manipulated online reviews.

Findings

A formal rationality pattern function for reviewers

Quantification of review trustworthiness based on rationality

Potential to identify manipulative or paid reviews

Abstract

In electronic commerce (e-commerce)markets, a decision-maker faces a sequential choice problem. Third-party intervention is essential in making purchase decisions in this choice process. For instance, while purchasing products/services online, a buyer's choice or behavior is often affected by the overall reviewers' ratings, feedback, etc. Moreover, the reviewer is also a decision-maker. The question that arises is how trustworthy these review reports and ratings are. The trustworthiness of these review reports and ratings is based on whether the reviewer is rational or irrational. Indexing the reviewer's rationality could be a way to quantify a reviewer's rationality, but it needs to communicate the history of their behavior. In this article, the researcher aims to derive a rationality pattern function formally and, thereby, the degree of rationality of the decision-maker or the reviewer in the sequential choice problem in the e-commerce markets. Applying such a rationality pattern function could make quantifying the rational behavior of an agent participating in the digital markets easier. This, in turn, is expected to minimize the information asymmetry within the decision-making process and identify the paid reviewers or manipulative reviews.