App Store Mining is Not Enough

被引：15
|
作者：
Nayebi, Maleknaz [1 ]
Farrahi, Homayoon [1 ]
Ruhe, Guenther [1 ]
Cho, Henry [2 ]
机构：
[1] Univ Calgary, SEDS Lab, Calgary, AB, Canada
[2] Univ Toronto, Dept Engn Sci, Toronto, ON, Canada
来源：
PROCEEDINGS OF THE 2017 IEEE/ACM 39TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING COMPANION (ICSE-C 2017) | 2017年
基金：
加拿大自然科学与工程研究理事会;
关键词：
App store mining; Twitter; Mobile apps; Topic modeling; Machine learning;
D O I：
10.1109/ICSE-C.2017.77
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
App store reviews are currently the main source of information for analyzing different aspects of app development and evolution. However, app users' feedback do not only occur on the app store. In fact, a large quantity of posts about apps are made daily on social media. In this paper, we study how Twitter can provide complementary information to support mobile app development. By analysing a total of 70 apps over a period of six weeks, we show that 22.4% more feature requests and 12.89% more bug reports could be found on Twitter.
引用
收藏
页码：152 / 154
页数：3
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