Targeting Methodologies

Overview:
Identify and target Wikipedia editors abusing their position by analyzing text patterns, usernames, and technical data through data breach analysis, fingerprinting, HUMINT, and technical targeting.

Fingerprinting:
Text Analysis: Use NLP to identify writing style, repeated phrases, and content patterns.
Cross-Article Comparison: Detect similarities in multiple articles, focusing on propagandist themes.
Behavioral Patterns: Analyze edit frequency, topic focus, and collaboration behavior.
Historical Comparison: Track revert-and-restore behavior for coordinated agenda.

Username Analysis and Dataset Correlation:
Username Profiling: Analyze naming patterns and cross-reference usernames across platforms.
Reuse in Breached Data: Search breached datasets for reused names, emails, and online identities.
Cross-Platform Analysis: Identify connections between usernames and other online activities

The Heritage Foundation plans to “identify and target” volunteer editors on Wikipedia who it says are “abusing their position” by publishing content the group believes to be antisemitic, according to documents obtained by the Forward.

Employees of Heritage, the conservative think tank that produced the Project 2025 policy blueprint for the second Trump administration, said they plan to use facial recognition software and a database of hacked usernames and passwords in order to identify contributors to the online encyclopedia, who mostly work under pseudonyms. It’s not clear exactly what kind of antisemitism the Wikipedia effort, which has not been previously reported, is intended to address. But in recent months some Jewish groups have complained about a series of changes on the website relating to Israel, the war in Gaza and its repercussions.