Datasets:
language:
- en
license: mit
task_categories:
- time-series-forecasting
tags:
- temporal-point-process
- event-sequences
- wikipedia
- edit-history
- collaborative-editing
- marked-temporal-point-process
size_categories:
- n<1K
Wikipedia Edit Events
Curated Wikipedia article edit history sequences from Featured and Good articles, designed for temporal point process (TPP) and marked temporal point process (MTPP) modeling. Each sequence tracks an article's editorial activity over time, where the prediction target is the edit action type.
Dataset Description
- Source: Wikipedia MediaWiki API
- Article source: Wikipedia Featured + Good articles
- Grouping: Per-article, chunked into consecutive sequences of 60–80 events
- Sequences: 276
- Sequence length: 63–80 events per sequence (mean: 79.9)
- Event types: 6 edit action types
- Time unit: hours
- Duration range: 2.9–4,319 hours (mean: 1,061 hours ≈ 44 days, capped at 6 months)
Schema
Each record is a dictionary with 8 fields:
| Field | Type | Description |
|---|---|---|
seq_idx |
int | Sequence index |
seq_len |
int | Number of events in the sequence |
description |
str | Natural language description of the article's edit timeline |
metadata |
str (JSON) | article_title, article_pageid, chunk_index, num_editors, date_range_start, date_range_end, time_unit |
time_since_start |
list[float] | Time since the first event (in hours) |
time_since_last_event |
list[float] | Time since the previous event (in hours) |
type_event |
list[str] | Edit action type label (see below) |
type_text |
list[str] | Natural language description of each edit |
Event Types (6 edit action types)
Edits are classified by priority order from revision metadata (byte delta, tags, edit summary):
| Type | Description | Classification Rule |
|---|---|---|
revert |
Undoing a previous edit | Tags contain mw-rollback, mw-undo, or mw-manual-revert |
reference |
Adding or modifying citations | Edit summary matches ref/cite/source/bibliography patterns |
content_addition |
Substantial new content | Byte delta > +200 |
content_removal |
Substantial content removed | Byte delta < -200 |
copy_edit |
Small wording/formatting changes | |delta| <= 200, not flagged as minor |
minor_edit |
Trivial corrections | Minor flag set |
Curation Filters
Sequences are aggressively filtered to ensure diverse, non-trivial edit type distributions:
| Filter | Value | Description |
|---|---|---|
max-articles |
1,000 | Featured + Good articles processed |
min-seq-size |
60 | Min events per sequence chunk |
max-seq-size |
80 | Max events per sequence chunk |
min-types |
4 | At least 4 distinct edit types per sequence |
max-duration-hours |
4,380 | Drop sequences spanning more than 6 months |
max-dominant-ratio |
0.40 | Drop sequences where any single type exceeds 40% |
max-repeat-ratio |
0.40 | Drop sequences where consecutive repeat ratio exceeds 40% |
Additional processing:
- Bot edits excluded (tag "bot" or username ending in "bot")
- Byte deltas computed from consecutive revision sizes
- Sequences chunked chronologically per article
Event Text
Each event's type_text is a coherent natural sentence providing rich context without explicitly stating the edit type classification. The article title is omitted (available at sequence level in description and metadata).
Registered editor My love is love made a moderate addition (+620 bytes, <1% of article) to section "Titling and artwork"
Sentence structure: {Editor identity} {size action} [to section "..."]. [Summary: "..."]. [Signals]. [Tool]. [Minor flag].
Components (included only when present):
- Editor identity (lead) —
"Registered editor Centrx"or"An anonymous editor" - Size action (verb) —
"made a substantial addition (+1,253 bytes, 61% of article)" - Section target —
to section "Background and formation"(extracted from edit comment) - Edit summary —
Summary: "start background"(cleaned of wiki markup) - Semantic signals — auto-detected patterns (e.g., "The summary mentions fixing language or typography")
- Tool/interface —
"Made using the visual editor"(from revision tags) - Minor flag —
"Flagged as minor"
The model must learn to predict the edit action type from these contextual signals.
Example
{
"seq_idx": 2,
"seq_len": 80,
"description": "Wikipedia edit timeline for the article '4 (Beyoncé album)' spanning Dec 2011 to Jan 2012. This sequence tracks editorial activity including content changes, reverts, and maintenance edits.",
"metadata": "{\"article_title\": \"4 (Beyoncé album)\", \"article_pageid\": 31176601, \"chunk_index\": 24, \"num_editors\": 22, \"date_range_start\": \"2011-12-13T16:21:57+00:00\", \"date_range_end\": \"2012-01-07T21:12:43+00:00\", \"time_unit\": \"hours\"}",
"time_since_start": [0.0, 0.22, 2.56, ...],
"time_since_last_event": [0.0, 0.22, 2.35, ...],
"type_event": ["content_addition", "minor_edit", "copy_edit", ...],
"type_text": [
"Registered editor My love is love made a moderate addition (+620 bytes, <1% of article) to section \"Titling and artwork\"",
"Registered editor My love is love made a null edit (no size change) to section \"Music and themes\". Flagged as minor",
"Registered editor Dumb + dumb = 4 made a small removal (-142 bytes)",
...
]
}
Intended Use
- Training and evaluating temporal point process models
- Studying collaborative editing patterns on Wikipedia
- Benchmarking next-event prediction and event forecasting
- Modeling marked temporal point processes with rich text marks
Citation
If you use this dataset, please cite:
@dataset{wikipedia_edit_events_2025,
title={Wikipedia Edit Events},
author={XiaoBB},
year={2025},
url={https://huggingface.co/datasets/DescribeEvents/wikipedia_edit_events},
note={Curated from Wikipedia MediaWiki API, Featured and Good articles}
}