# TokTrack: A Complete Token Provenance and Change Tracking Dataset for the English Wikipedia

## TL;DR

This paper introduces TokTrack, a comprehensive dataset capturing every token's creation, deletion, and re-addition history in English Wikipedia articles up to 2016, enabling detailed provenance and conflict analysis.

## Contribution

The paper presents a novel, large-scale dataset that tracks token-level provenance and changes in Wikipedia, facilitating new research in content evolution and editor interactions.

## Key findings

- Enables detailed token provenance analysis
- Allows measurement of content survival over time
- Facilitates analysis of editor conflicts and reverts

## Abstract

We present a dataset that contains every instance of all tokens (~ words) ever written in undeleted, non-redirect English Wikipedia articles until October 2016, in total 13,545,349,787 instances. Each token is annotated with (i) the article revision it was originally created in, and (ii) lists with all the revisions in which the token was ever deleted and (potentially) re-added and re-deleted from its article, enabling a complete and straightforward tracking of its history. This data would be exceedingly hard to create by an average potential user as it is (i) very expensive to compute and as (ii) accurately tracking the history of each token in revisioned documents is a non-trivial task. Adapting a state-of-the-art algorithm, we have produced a dataset that allows for a range of analyses and metrics, already popular in research and going beyond, to be generated on complete-Wikipedia scale; ensuring quality and allowing researchers to forego expensive text-comparison computation, which so far has hindered scalable usage. We show how this data enables, on token-level, computation of provenance, measuring survival of content over time, very detailed conflict metrics, and fine-grained interactions of editors like partial reverts, re-additions and other metrics, in the process gaining several novel insights.