Twitter User Gender Classification (CrowdFlower)
20,050 Twitter profiles from October 2015, each with one random tweet, released by CrowdFlower (Data for Everyone): crowd workers looked at each profile and judged whether the account belongs to a woman (6,700), a man (6,194) or a brand (5,942), with a confidence score; 1,117 could not be told. Each row has the tweet, the profile description, profile colours and counts. The tweet IDs in the original file were saved in scientific notation, so the tweets cannot be fetched again. Useful for author profiling, gender inference and telling people from brands. Licensed CC BY 4.0 by Figure Eight; it contains screen names and profile descriptions.
Cite this dataset at
twitter-gender-classifier.echo.directory
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- female6.7K (33.6%)
- male6.2K (31.0%)
- brand5.9K (29.8%)
- unknown1.1K (5.6%)
Computed over the full corpus.
Record
- Catalog key
twitter-gender-classifier- Authors
- CrowdFlower
- Year
- 2015
- Source paper
- Twitter User Gender Classification
- License
- CC BY 4.0 (Figure Eight 'Data for Everyone' library) (CC-BY-4.0)
- Records
- 20,050
- Nodes are
- unknown
- Edges are
- unknown
- Text corpus
- tweet text
- Languages
- en
- Collected
- 2015-10-26 to 2015-10-26 (2010s)
- Tasks
- Text classification (multi-class;
gender_label) inferred - Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://www.kaggle.com/datasets/crowdflower/twitter-user-gender-classification link checked
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}
}
@misc{crowdflower2015twitteruserg,
title = {Twitter User Gender Classification},
author = {CrowdFlower},
year = {2015},
note = {Data for Everyone library, added 2015-11-15},
howpublished = {\url{https://www.figure-eight.com/data-for-everyone/}}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
CrowdFlower (2015). Twitter User Gender Classification (CrowdFlower) [Data set]. https://twitter-gender-classifier.echo.directory/
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
CrowdFlower. Twitter User Gender Classification (CrowdFlower). 2015, twitter-gender-classifier.echo.directory/.