SenWave: COVID-19 Tweets Labelled for Ten Sentiments
SenWave: tweets about COVID-19 labeled for ten sentiments, by Qiang Yang and colleagues. The package holds 10,000 English tweets and 9,999 Arabic tweets that annotators labeled with any of ten emotions (optimistic, thankful, empathetic, pessimistic, anxious, sad, annoyed, denial, official report, joking), and Spanish, French and Italian versions of the 10,000 English tweets that the authors made with Google Translate, each carrying the English labels. The Arabic tweets also carry one of four overall sentiment labels (neutral 4,269, negative 2,750, positive 1,562, joking 1,418). That is 49,999 labeled tweets in five languages. The tweets were collected from 1 March 2020 (per the upstream README). The upstream repository also lists a large number of unlabeled tweet IDs; they are not part of these files. The files have no usable tweet IDs and no users, times or other fields.
Cite this dataset at
senwave.echo.directory
Analytics
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- 1joking
- 2annoyed
- 3optimistic
- 4sad
- 5official report
- 6anxious
- 7pessimistic
- 8denial
- 9thankful
- 10empathetic
- 1en
- 2es
- 3fr
- 4it
- 5ar
Computed over the full corpus.
Record
- Catalog key
senwave- Authors
- Yang, Qiang; Alamro, Hind; Albaradei, Somayah; Salhi, Adil; Lv, Xiaoting; Ma, Changsheng; Alshehri, Manal; Jaber, Inji; Tifratene, Faroug; Wang, Wei; Gojobori, Takashi; Duarte, Carlos M.; Gao, Xin; Zhang, Xiangliang
- Year
- 2020
- Source paper
- SenWave: Monitoring the Global Sentiments under the COVID-19 Pandemic
- DOI / arXiv
- 10.48550/arXiv.2006.10842
- License
- Apache-2.0 (repository); the README restricts use to non-commercial research (LicenseRef-Research-Only)
- Records
- 49,999
- Nodes are
- unknown
- Edges are
- unknown
- Text corpus
- tweet text
- Languages
- ar, en, es, fr, it
- Collected
- 2020-03-01 to 2020-05-15 (2020s)
- Tasks
- Sentiment classification inferred, Emotion classification (multi-label;
emotion_optimistic, emotion_thankful, emotion_empathetic, emotion_pessimistic, emotion_anxious, emotion_sad, emotion_annoyed, emotion_denial, emotion_official_report, emotion_joking) inferred - Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://github.com/gitdevqiang/SenWave link checked
- Original files as received
- The source files, unconverted, kept for reference: mirrored on echo.directory on 2026-10-20, 7.2 MB across 7 files. Checksums in MANIFEST.json. For use, start with the data package below.
- Data package
- Version 1.0.0 of this dataset as an ECHO Data Package: posts (49,999 rows), annotations (94,123 rows).
- Structure
- Labelled data, Text
How to cite
BibTeX
@misc{echo2026,
title = {ECHO: Exploratory Compendium of Humanity Online},
author = {Switzer, Braden and Zafarani, Reza},
year = {2026},
url = {https://echo.directory},
note = {Syracuse University}
}
@article{yang2020senwave,
title = {SenWave: Monitoring the Global Sentiments under the COVID-19 Pandemic},
author = {Yang, Qiang and others},
journal = {arXiv preprint arXiv:2006.10842},
year = {2020}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Yang, Q., Alamro, H., Albaradei, S., Salhi, A., Lv, X., Ma, C., Alshehri, M., Jaber, I., Tifratene, F., Wang, W., Gojobori, T., Duarte, C. M., Gao, X., & Zhang, X. (2020). SenWave: COVID-19 Tweets Labelled for Ten Sentiments [Data set]. https://doi.org/10.48550/arXiv.2006.10842
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Yang, Qiang, et al. SenWave: COVID-19 Tweets Labelled for Ten Sentiments. 2020, doi.org/10.48550/arXiv.2006.10842.