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

2021

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.

Paper Citation

in Harvard Style

Mathews C., Ye K., Grozdanovski J., Marinelli M., Zhong K., Khalajzadeh H., Obie H. and Grundy J. (2021). AH-CID: A Tool to Automatically Detect Human-Centric Issues in App Reviews. In Proceedings of the 16th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-523-4, pages 386-397. DOI: 10.5220/0010576503860397

in Bibtex Style

@conference{icsoft21,
author={Collins Mathews and Kenny Ye and Jake Grozdanovski and Marcus Marinelli and Kai Zhong and Hourieh Khalajzadeh and Humphrey Obie and John Grundy},
title={AH-CID: A Tool to Automatically Detect Human-Centric Issues in App Reviews},
booktitle={Proceedings of the 16th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2021},
pages={386-397},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010576503860397},
isbn={978-989-758-523-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - AH-CID: A Tool to Automatically Detect Human-Centric Issues in App Reviews
SN - 978-989-758-523-4
AU - Mathews C.
AU - Ye K.
AU - Grozdanovski J.
AU - Marinelli M.
AU - Zhong K.
AU - Khalajzadeh H.
AU - Obie H.
AU - Grundy J.
PY - 2021
SP - 386
EP - 397
DO - 10.5220/0010576503860397