AH-CID: a tool to automatically detect human-centric issues in app reviews

Collins Mathews, Kenny Ye, Jake Grozdanovski, Marcus Marinelli, Kai Zhong, Hourieh Khalajzadeh, Humphrey Obie, John Grundy

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

3 Citations (Scopus)

Abstract

In modern software development, there is a growing emphasis on creating and designing around the end-user. This has sparked the widespread adoption of human-centred design and agile development. These concepts intersect during the user feedback stage in agile development, where user requirements are re-evaluated and utilised towards the next iteration of development. An issue arises when the amount of user feedback far exceeds the team’s capacity to extract meaningful data. As a result, many critical concerns and issues may fall through the cracks and remain unnoticed, or the team must spend a great deal of time in analysing the data that can be better spent elsewhere. In this paper, a tool is presented that analyses a large number of user reviews from 24 mobile apps. These are used to train a machine learning (ML) model to automatically generate the probability of the existence of human-centric issues, to automate and streamline the user feedback review analysis process. Evaluation shows an improved ability to find human-centric issues of the users.

Original languageEnglish
Title of host publicationProceedings of the 16th International Conference on Software Technologies
EditorsHans-Georg Fill, Marten van Sinderen, Leszek Maciaszek
PublisherScitepress
Pages386-397
Number of pages12
ISBN (Electronic)9789897585234
DOIs
Publication statusPublished - 2021
EventInternational Conference on Software Technologies 2021 - Online
Duration: 6 Jul 20218 Jul 2021
Conference number: 16th
https://www.scitepress.org/ProceedingsDetails.aspx?ID=VnrgMHENH6Q=&t=1 (Proceedings)

Publication series

NameProceedings of the 16th International Conference on Software Technologies, ICSOFT 2021
PublisherScitepress
Volume1
ISSN (Electronic)2184-2833

Conference

ConferenceInternational Conference on Software Technologies 2021
Abbreviated titleICSOFT 2021
Period6/07/218/07/21
Internet address

Keywords

  • App Reviews
  • End-user
  • Human-centred Design
  • Human-centric Issues
  • Machine Learning

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