Mining the participatory role of massive user reviews in the update design of APP software

QIAN Yu, CAO Enye, DENG Wenjun, YUAN Hua

Systems Engineering - Theory & Practice ›› 2021, Vol. 41 ›› Issue (3) : 554-564.

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Systems Engineering - Theory & Practice ›› 2021, Vol. 41 ›› Issue (3) : 554-564. DOI: 10.12011/SETP2019-1136

Mining the participatory role of massive user reviews in the update design of APP software

  • QIAN Yu, CAO Enye, DENG Wenjun, YUAN Hua
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Abstract

The user reviews published on APP market contain useful information for the APP R&D team. In order to study the influence and mode of user reviews on APP software update design, we propose a sentence vector similarity calculation model based on word vector representation, which can be used to measure the similarity of sentences from update log text and user comment text. Then, we propose a "log-comment" matching algorithm to divide the different semantic matching result into different data sets. By collecting a large amount of APP software update logs and user reviews from an open APP market, our method found that the APP development team adopted less than 20% of the user reviews, and the content adopted was mainly focused on the APP software function. Many of the user reviews pointed to the marketing activities, however, these reviews can rarely be considered and corrected in the new version of an APP. It was partly due to the limited role of R&D team in company's daily operation.

Key words

text mining / APP software / update design / user review

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QIAN Yu , CAO Enye , DENG Wenjun , YUAN Hua. Mining the participatory role of massive user reviews in the update design of APP software. Systems Engineering - Theory & Practice, 2021, 41(3): 554-564 https://doi.org/10.12011/SETP2019-1136

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Funding

National Natural Science Foundation of China (71490723, 91846105, 71572029, 71671027)
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