The impact of mobile application information on application download: A text mining approach

Ying Wang, Jaeki Song

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The effects of customers' reviews on products have been understood in the initial digital purchase context. This study extends this literature by exploring the reviews in the mobile environment. It calls for understanding the context of reviews which types of information in the review have significant impact on customers' behavior. This study applied text mining in analyzing customers' reviews in purchasing mobile applications and find out important applications' features valuable for customers by discovering meaningful information in influential words. We find that for mobile applications, specific expressions in online customer review, companies' reply to the review, and quality certifications from application store have significant impacts on the number of download. Theoretical and practical implications are discussed.

Original languageEnglish
Title of host publication2015 Americas Conference on Information Systems, AMCIS 2015
PublisherAmericas Conference on Information Systems
ISBN (Electronic)9780996683104
StatePublished - 2015
Event21st Americas Conference on Information Systems, AMCIS 2015 - Fajardo, Puerto Rico
Duration: Aug 13 2015Aug 15 2015

Publication series

Name2015 Americas Conference on Information Systems, AMCIS 2015

Conference

Conference21st Americas Conference on Information Systems, AMCIS 2015
CountryPuerto Rico
CityFajardo
Period08/13/1508/15/15

Keywords

  • Customers' review
  • Latent semantic analysis
  • Mobile application
  • Text mining

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