TY - GEN
T1 - App Reviews: Breaking the User and Developer Language Barrier
AU - Hoon, Leonard
AU - Rodriguez-Garcia, Miguel Angel
AU - Vasa, Rajesh
AU - Valencia-García, Rafael
AU - Schneider, Jean-Guy
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2015/10/22
Y1 - 2015/10/22
N2 - Apple, Google and third party developers offer apps across over twenty categories for various smart mobile devices. Offered exclusively through the App Store and Google Play, each app allows users to review the app and their experience with it. Current literature offers a general statistical picture of these reviews, and a broad overview of the nature of discontent of apps. However, we do not yet have a good framework to classify user reviews against known software quality attributes like performance or usability. In order to close this gap, in this paper, we develop an ontology encompassing software attributes derived from software quality models. This decomposes into approximately five thousand words that users employ to review apps. By identifying a consistent set of vocabulary that users communicate with, we can sanitise large datasets to extract stakeholder actionable information from reviews. The findings offered in this paper assists future app review analysis by bridging end-user communication and software engineering vocabulary.
AB - Apple, Google and third party developers offer apps across over twenty categories for various smart mobile devices. Offered exclusively through the App Store and Google Play, each app allows users to review the app and their experience with it. Current literature offers a general statistical picture of these reviews, and a broad overview of the nature of discontent of apps. However, we do not yet have a good framework to classify user reviews against known software quality attributes like performance or usability. In order to close this gap, in this paper, we develop an ontology encompassing software attributes derived from software quality models. This decomposes into approximately five thousand words that users employ to review apps. By identifying a consistent set of vocabulary that users communicate with, we can sanitise large datasets to extract stakeholder actionable information from reviews. The findings offered in this paper assists future app review analysis by bridging end-user communication and software engineering vocabulary.
UR - http://hdl.handle.net/10754/622133
UR - http://link.springer.com/10.1007/978-3-319-26285-7_19
UR - http://www.scopus.com/inward/record.url?scp=84983196470&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-26285-7_19
DO - 10.1007/978-3-319-26285-7_19
M3 - Conference contribution
SN - 9783319262833
SP - 223
EP - 233
BT - Trends and Applications in Software Engineering
PB - Springer Nature
ER -