Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings - 2025 IEEE 33rd International Requirements Engineering Conference Workshops, REW 2025 |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| Seiten | 107-114 |
| Seitenumfang | 8 |
| ISBN (elektronisch) | 9798331538347 |
| ISBN (Print) | 979-8-3315-3835-4 |
| Publikationsstatus | Veröffentlicht - 1 Sept. 2025 |
| Veranstaltung | 33rd IEEE International Requirements Engineering Conference Workshops, REW 2025 - Valencia, Spanien Dauer: 1 Sept. 2025 → 5 Sept. 2025 |
Publikationsreihe
| Name | Proceedings - IEEE International Requirements Engineering Conference Workshops |
|---|---|
| ISSN (Print) | 2770-6826 |
| ISSN (elektronisch) | 2770-6834 |
Abstract
Sentiment analysis is an essential technique for investigating the emotional climate within developer teams, contributing to both team productivity and project success. Existing sentiment analysis tools in software engineering primarily rely on English or non-German gold-standard datasets. To address this gap, our work introduces a German dataset of 5,949 unique developer statements, extracted from the German developer forum Android-Hilfe.de. Each statement was annotated with one of six basic emotions, based on the emotion model by Shaver et al. [1], by four German-speaking computer science students. Evaluation of the annotation process showed high interrater agreement and reliability. These results indicate that the dataset is sufficiently valid and robust to support sentiment analysis in the German-speaking software engineering community. Evaluation with existing German sentiment analysis tools confirms the lack of domain-specific solutions for software engineering. We also discuss approaches to optimize annotation and present further use cases for the dataset.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Artificial intelligence
- Informatik (insg.)
- Software
- Ingenieurwesen (insg.)
- Sicherheit, Risiko, Zuverlässigkeit und Qualität
- Mathematik (insg.)
- Modellierung und Simulation
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- BibTex
- RIS
Proceedings - 2025 IEEE 33rd International Requirements Engineering Conference Workshops, REW 2025. Institute of Electrical and Electronics Engineers Inc., 2025. S. 107-114 (Proceedings - IEEE International Requirements Engineering Conference Workshops).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - A German Gold-Standard Dataset for Sentiment Analysis in Software Engineering
AU - Obaidi, Martin
AU - Herrmann, Marc
AU - Schmid, Elisa
AU - Ochsner, Raymond
AU - Schneider, Kurt
AU - Klünder, Jil
N1 - Publisher Copyright: © 2025 IEEE.
PY - 2025/9/1
Y1 - 2025/9/1
N2 - Sentiment analysis is an essential technique for investigating the emotional climate within developer teams, contributing to both team productivity and project success. Existing sentiment analysis tools in software engineering primarily rely on English or non-German gold-standard datasets. To address this gap, our work introduces a German dataset of 5,949 unique developer statements, extracted from the German developer forum Android-Hilfe.de. Each statement was annotated with one of six basic emotions, based on the emotion model by Shaver et al. [1], by four German-speaking computer science students. Evaluation of the annotation process showed high interrater agreement and reliability. These results indicate that the dataset is sufficiently valid and robust to support sentiment analysis in the German-speaking software engineering community. Evaluation with existing German sentiment analysis tools confirms the lack of domain-specific solutions for software engineering. We also discuss approaches to optimize annotation and present further use cases for the dataset.
AB - Sentiment analysis is an essential technique for investigating the emotional climate within developer teams, contributing to both team productivity and project success. Existing sentiment analysis tools in software engineering primarily rely on English or non-German gold-standard datasets. To address this gap, our work introduces a German dataset of 5,949 unique developer statements, extracted from the German developer forum Android-Hilfe.de. Each statement was annotated with one of six basic emotions, based on the emotion model by Shaver et al. [1], by four German-speaking computer science students. Evaluation of the annotation process showed high interrater agreement and reliability. These results indicate that the dataset is sufficiently valid and robust to support sentiment analysis in the German-speaking software engineering community. Evaluation with existing German sentiment analysis tools confirms the lack of domain-specific solutions for software engineering. We also discuss approaches to optimize annotation and present further use cases for the dataset.
KW - developer communication. machine learning
KW - requirements engineering
KW - sentiment analysis
UR - http://www.scopus.com/inward/record.url?scp=105020978330&partnerID=8YFLogxK
U2 - 10.1109/REW66121.2025.00018
DO - 10.1109/REW66121.2025.00018
M3 - Conference contribution
AN - SCOPUS:105020978330
SN - 979-8-3315-3835-4
T3 - Proceedings - IEEE International Requirements Engineering Conference Workshops
SP - 107
EP - 114
BT - Proceedings - 2025 IEEE 33rd International Requirements Engineering Conference Workshops, REW 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd IEEE International Requirements Engineering Conference Workshops, REW 2025
Y2 - 1 September 2025 through 5 September 2025
ER -