Awesome!: conveying satisfaction on the app store

Authors:
Leonard Hoon;Rajesh Vasa;Gloria Yoanita Martino;Jean-Guy Schneider;Kon Mouzakis
Affiliations:
Swinburne University of Technology, Melbourne, Australia;Swinburne University of Technology, Melbourne, Australia;Swinburne University of Technology, Melbourne, Australia;Swinburne University of Technology, Melbourne, Australia;Swinburne University of Technology, Melbourne, Australia
Venue:
Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration
Year:
2013

Citing 8
Cited 0

Understanding user evaluations of information systems

Management Science
Mining and summarizing customer reviews

Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
User Interface Design and Evaluation (The Morgan Kaufmann Series in Interactive Technologies) (The Morgan Kaufmann Series in Interactive Technologies)

User Interface Design and Evaluation (The Morgan Kaufmann Series in Interactive Technologies) (The Morgan Kaufmann Series in Interactive Technologies)
Micro-blogging as online word of mouth branding

CHI '09 Extended Abstracts on Human Factors in Computing Systems
Software engineering issues for mobile application development

Proceedings of the FSE/SDP workshop on Future of software engineering research
Perceived usefulness, perceived ease of use, and user acceptance of information technology

MIS Quarterly
A preliminary analysis of mobile app user reviews

Proceedings of the 24th Australian Computer-Human Interaction Conference
A preliminary analysis of vocabulary in mobile app user reviews

Proceedings of the 24th Australian Computer-Human Interaction Conference

Quantified Score

Hi-index	0.00

Visualization

Abstract

In a competitive market like the App Store, high user perceived quality is paramount, especially due to the public review system offered. These reviews give developers feedback on their own apps, as well as help provide data for competitor analysis. However, given the size of the data set, manual analysis of reviews is unrealistic, especially given the need for a rapid response to changing market dynamics. Current research into mobile app reviews has provided an insight into the statistical distributions, but there is minimal knowledge about the content in these reviews. In particular, we do not know if the aggregated numerical rating is a reliable indicator of the information within a review. This work reports on an analysis of reviews to determine how closely aligned the numerical ratings are to the textual description. We observed that short user reviews mostly contain a small set of words, and the corresponding numerical rating matches the underlying sentiment.