Integrating sentiment analysis into agile feedback loops for continuous improvement

Marçal, Diogo; Metrôlho, J.C.M.M; Ribeiro, Fernando Reinaldo

Publication

Integrating sentiment analysis into agile feedback loops for continuous improvement

2025Research article

datacite.subject.fos	Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
dc.contributor.author	Marçal, Diogo
dc.contributor.author	Metrôlho, J.C.M.M
dc.contributor.author	Ribeiro, Fernando Reinaldo
dc.contributor.editor	Gasparetto , Alessandro
dc.contributor.editor	O’Shaughnessy, Douglas
dc.date.accessioned	2025-12-10T15:52:25Z
dc.date.available	2025-12-10T15:52:25Z
dc.date.issued	2025
dc.description	The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.
dc.description.abstract	The pursuit of continuous improvement is a defining feature of agile software development, yet its success depends on the systematic collection and interpretation of team members’ feedback. Conventional mechanisms, such as retrospectives and surveys, provide valuable insights but are often constrained by their episodic nature and susceptibility to subjective interpretation. This study examines the potential of Artificial Intelligence (AI), and in particular sentiment analysis, to complement feedback-driven practices and strengthen continuous improvement in agile contexts. Two literature reviews were conducted: one on applications of AI across software engineering domains and another focusing specifically on sentiment analysis in agile environments. Based on these insights, a prototype tool was developed to integrate sentiment analysis into task management workflows, enabling the structured collection and analysis of developers’ perceptions of task descriptions. Semi-structured interviews with experienced project managers confirmed the relevance of this approach, highlighting its capacity to improve task clarity and foster more transparent and inclusive feedback processes. Participants emphasized the value of the proposed approach in generating rapid, automated insights, while also identifying potential limitations related to response fatigue and the reliability of AI-generated outcomes. The findings suggest that incorporating sentiment analysis into agile practices is both feasible and advantageous, providing a pathway to align technical objectives with developer experiences while enhancing motivation, collaboration, and operational efficiency.	eng
dc.identifier.citation	MARÇAL, D. [et al.] (2025) - Integrating sentiment analysis into agile feedback loops for continuous improvement. Applied Sciences, 15:22, p. 12329. DOI: 10.3390/app152212329
dc.identifier.doi	10.3390/app152212329
dc.identifier.issn	2076-3417
dc.identifier.uri	http://hdl.handle.net/10400.11/10400
dc.language.iso	eng
dc.peerreviewed	yes
dc.publisher	MDPI, Basel, Switzerland
dc.relation.hasversion	https://www.mdpi.com/2076-3417/15/22/12329
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.subject	agile software development
dc.subject	continuous improvement
dc.subject	feedback analysis
dc.subject	sentiment analysis
dc.subject	task description quality
dc.title	Integrating sentiment analysis into agile feedback loops for continuous improvement	eng
dc.type	research article
dspace.entity.type	Publication
oaire.citation.title	Applied Sciences
oaire.version	http://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyName	Metrôlho
person.familyName	Reinaldo Silva Garcia Ribeiro
person.givenName	José Carlos
person.givenName	Fernando
person.identifier	1688084
person.identifier.ciencia-id	4B17-3AF4-7DD4
person.identifier.ciencia-id	7B1C-D761-291D
person.identifier.orcid	0000-0002-7327-2109
person.identifier.orcid	0000-0002-1225-3844
person.identifier.scopus-author-id	6507997502
relation.isAuthorOfPublication	195ac9ea-6661-4217-addf-ac4bc5225f90
relation.isAuthorOfPublication	165761b1-f958-4c13-b53f-ef0a4dde1d97
relation.isAuthorOfPublication.latestForDiscovery	195ac9ea-6661-4217-addf-ac4bc5225f90