Antramic product workflow
Understand How Viewers Feel About Your Videos
Review positive, neutral, mixed, and critical audience reactions alongside the comments that informed each result, rather than relying on a score alone.
Sentiment with context
Compare reactions across your own videos, identify language that may be ambiguous, and inspect evidence before using a result in a content or community decision.
Designed for responsible review
Sentiment is an AI-assisted classification, not a fact about a person. Antramic keeps uncertainty and supporting examples visible so creators can apply judgment.
Read categories with their evidence
Open representative comments from each sentiment group and check what prompted the reaction. Praise for a topic, criticism of audio, and frustration with an unanswered question may all require different actions even when a model assigns them the same broad label.
Compare like with like
Use comparable videos, publishing periods, languages, and comment samples when reviewing changes. A different audience mix or topic can explain a shift, so sentiment percentages should not be treated as a controlled experiment or an official YouTube performance metric.
Keep language and uncertainty visible
Sarcasm, jokes, slang, mixed sentiment, and short replies can be difficult to classify. Treat unclear examples as uncertain, correct obvious mistakes, and use the grouped result to guide closer reading rather than to label individual viewers or infer personal characteristics.