research-article

A preliminary analysis of mobile app user reviews

Authors:

Rajesh Vasa,

Leonard Hoon,

Kon Mouzakis,

Akihiro NoguchiAuthors Info & Claims

OzCHI '12: Proceedings of the 24th Australian Computer-Human Interaction Conference

Pages 241 - 244

https://doi.org/10.1145/2414536.2414577

Published: 26 November 2012 Publication History

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Abstract

The advent of online software distribution channels like Apple Inc.'s App Store and Google Inc.'s Google Play has offered developers a single, low cost, and powerful distribution mechanism. These online stores help users discover apps as well as leave a review. Ratings and reviews add value to both the developer and potential new users by providing a crowd-sourced indicator of app quality. Hence, for developers it is important to get positive reviews and high ratings to ensure that an app has a viable future. But, what exactly do users say on these app stores? And more importantly, what is the experience that compels a user to leave either a positive or a negative rating? Our analysis of 8.7 million reviews from 17,330 apps shows that users tend to leave short, yet informative reviews, and the rating as well as the category influences the length of a review. In this preliminary study, we found that users will leave longer messages when they rate an app poorly, and the depth of feedback in certain categories is significantly higher than for other.

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Index Terms

A preliminary analysis of mobile app user reviews
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Information systems
  1. Information retrieval
    1. Document representation
      1. Content analysis and feature selection
  2. Information systems applications
    1. Data mining

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Published In

OzCHI '12: Proceedings of the 24th Australian Computer-Human Interaction Conference

November 2012

692 pages

ISBN:9781450314381

DOI:10.1145/2414536

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 November 2012

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OzCHI '12

Sponsor:

Human Factors & Ergonomics Soc

OzCHI '12: The 24th Australian Computer-Human Interaction Conference

November 26 - 30, 2012

Melbourne, Australia

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Overall Acceptance Rate 362 of 729 submissions, 50%

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Guluzade LSas C(2024)Functionality and User Review Analysis of Mobile Apps for Mindfulness Eating and Eating DisordersProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661521(1350-1371)Online publication date: 1-Jul-2024
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