Indian marriage on Reddit: the aggregate data

The aggregate counts behind Indian marriage on Reddit: what 391,459 records show, as CSV and JSON, with a data package describing every field. Derived from 391,459 public Reddit records published 2024-09-02 to 2026-09-02. How they were produced is in the method note.

Why there is no record-level release

Prevow will not publish the raw corpus, raw excerpts, or anything at record level. Checking whether the source's redaction pass worked, rather than whether it ran, found 18 of 391,459 records still carrying an identifier, one of them naming a private individual in identifying detail. A redaction pass with demonstrated holes cannot be the basis of a record-level release. Everything here is an aggregate, and no figure in it can be reduced to an individual record.

The files

• topic-labels.csv. Every topic label in the taxonomy, counted as primary and in any position, over all records. 26 rows.
• posts-by-topic-label.csv. Topic labels across posts only, primary and any position, with percentages of the post count. 26 rows.
• comments-by-topic-label.csv. Topic labels across comments only, primary and any position. 26 rows.
• subreddits.csv. Posts and comments by contributing subreddit, with comments per post. 64 rows.
• subreddit-shares-cleaned.csv. Subreddit share of the corpus before and after removing non-participant comments. 30 rows.
• topic-by-subreddit.csv. Topic label by subreddit. Cells below thirty are uninterpretable and marked. 624 rows.
• topic-by-gender.csv. Topic label by stated gender. Describes the four posts in ten that state one. 105 rows.
• topic-by-relationship-stage.csv. Topic label by stated relationship stage. 133 rows.
• quarterly-topic-series.csv. Topic label by calendar quarter. Coverage, not discussion volume; first and last quarters are truncated. 226 rows.
• quarter-totals.csv. Posts per calendar quarter. 9 rows.
• verdicts.csv. How the tested patterns scored under adversarial testing. 6 rows.
• unlabelled-subjects.csv. Subjects present in the records with no taxonomy label, counted by term search. Lower bounds. 9 rows.
• targeted-searches.csv. The ten searches written to find the exception to a claim, with their hit counts. 10 rows.
• aggregate-counts.json. Every published table and keyed count in one file, with the corpus facts and their denominators. 67 keyed counts.
• claim-ledger.csv. All logged claims with their verdicts, whether each is published, and what it would take to publish the rest. Supporting record identifiers are removed. 111 rows.

datapackage.json describes every file and field, with a SHA-256 checksum for each.

Reading these files

• Every percentage divides by a stated denominator, and the denominator is in the column name.
• Primary and any-position counts are different things. A record carries one primary label and up to eight secondary ones, so any-position counts do not sum to the corpus size.
• Two labels never appear as primary. They are context flags, and treating either as a subject volume double-counts.
• Cells below thirty are uninterpretable and are marked in the files.
• The quarterly series is coverage, not discussion volume. The first and last quarters are truncated, and no trend claim is available from this corpus.
• The source tier field is not a quality filter.

Licence

These aggregate counts, and the charts drawn from them, are published under CC BY 4.0. Reuse them, including commercially, with attribution to Prevow and a link to the report.

Citing the data

Prevow (2026). Indian marriage on Reddit: aggregate counts over 391,459 public Reddit records, 2024-09-02 to 2026-09-02. https://prevow.app/research/indian-marriage-reddit-study-2026-data