Software reviews are verified to be a good source of users’ experience.
The software “quality in use” concerns meeting users’ needs. Current
software quality models such as McCall and Boehm, are built to support software
development process, rather than users perspectives. In this paper, opinion
mining is used to extract and summarize software “quality in use” from software
reviews. A framework to detect software “quality in use” as defined by the
ISO/IEC 25010 standard is presented here. The framework employs opinionfeature
double propagation to expand predefined lists of software “quality in
use” features to domain specific features. Clustering is used to learn software
feature “quality in use” characteristics group. A preliminary result of extracted
software features shows promising results in this direction
