How RageCheck detects manipulative patterns in content.
RageCheck uses a two-stage analysis pipeline: rule-based pattern detection followed by optional AI-powered contextual analysis. This hybrid approach balances speed, transparency, and accuracy.
The system analyzes text for linguistic patterns commonly associated with manipulative framing—language designed to provoke emotional reactions rather than inform. It does not assess factual accuracy or political bias.
Content is analyzed across five distinct signal categories, each targeting specific manipulation patterns:
Emotionally charged words designed to provoke reactions rather than convey information.
Examples: Dehumanizing terms, inflammatory adjectives, insults disguised as descriptors, words that presuppose guilt or malice.
Black-and-white language that eliminates nuance and complexity.
Examples: "Always," "never," "everyone knows," "no one can deny," "the only way," "completely," "totally."
Fear-mongering language that emphasizes danger, catastrophe, or existential threats.
Examples: "Dangerous," "threat," "crisis," "catastrophe," "destroy," "end of," "collapse," urgent calls to action based on fear.
Tribal language that creates artificial divisions between groups.
Examples: "They want to," "those people," "the elite," "real Americans," "our side," "the enemy," collective blame attribution.
Phrases designed to maximize clicks, shares, and emotional responses.
Examples: "You won't believe," "share this before," "what happens next," "the truth about," "what they don't want you to know."
The first stage uses pattern matching against curated dictionaries of manipulative phrases. Each category has weighted terms—stronger manipulative signals receive higher weights.
Scores are normalized per 1,000 words to account for content length, ensuring short tweets and long articles are compared fairly.
When available, Claude AI reviews the rule-based findings to add context. This stage can adjust scores based on factors rules can't capture:
Minimal manipulation signals
Some concerning patterns
Significant manipulation density