The Impact of Mobile Application Information on Application Download: A Text Mining Approach

نویسندگان

  • Jaeki Song
  • Ying Wang
چکیده

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.

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تاریخ انتشار 2015