Affiliation:
1. University of Wisconsin Oshkosh
2. University of Illinois Springfield
Abstract
Abstract
Large volumes of app reviews generated by online users have strategic value for app providers. We investigate how Fin app users consider information security and privacy in their reviews and how these concerns affect the app’s performance in terms of its overall rating. We used 71,044 online reviews from multiple Fin apps in the digital market. We analyzed the unstructured data by conducting a textual analysis and developed a semi-supervised machine-learning model to extract insights regarding how users perceive security and privacy. The main results showed that perceived concerns about security and privacy negatively affect the apps' performance.
Publisher
Research Square Platform LLC