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Caveat emptor, computational social science: Large-scale missing data in a widely-published Reddit corpus.
Devin Gaffney1, J Nathan Matias2
1Network Science Institute, Northeastern University, Boston, Massachusetts, United States of America.
Plos One
|July 7, 2018
Summary
A widely used Reddit comment dataset has significant data gaps, potentially biasing computational social science research. Researchers should carefully consider these limitations, especially for user history and network analysis.
Area of Science:
- Computational Social Science
- Data Integrity
- Social Behavior Research
Background:
- Computational social science relies on accurate data for valid research.
- A dataset claiming all public Reddit comments was widely adopted for academic studies.
- This data underpins research in machine learning, social behavior, politics, and more.
Purpose of the Study:
- To document the "every publicly available Reddit comment" dataset.
- To identify and analyze substantial gaps and limitations within this dataset.
- To assess the risks these data deficiencies pose to research validity.
Main Methods:
- Dataset documentation and analysis.
- Identification of missing observations.
- Risk assessment for various research methodologies.
Main Results:
- Substantial gaps and limitations were discovered in the Reddit comment dataset.
- Missing data poses risks to research validity, particularly for user history and network analysis.
- Moderate risks exist for participation count comparisons, and lesser risks for machine learning studies avoiding representational claims.
Conclusions:
- The integrity of the widely used Reddit comment dataset is compromised by significant omissions.
- Researchers must be aware of these limitations to mitigate bias in computational social science.
- Careful consideration of data gaps is crucial for valid findings in social behavior and related fields.
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