Supporting work · Audience insight · YouTube
A 50,000-comment sentiment analysis
A Beast Philanthropy video featuring The Phoenix, a partner in Stand Together’s network, drew 50,338 comments. The corpus could be used to measure participation, map recurring audience themes, and identify the limits of what the data could support.
The work
Sole author and analyst. I treated the comment section as primary audience data: I normalized spelling, punctuation, capitalization, and spacing variants of the video’s “Together We Rise” call to action and counted 2,270 instances, roughly 4.5% of all comments. I then mapped the recurring discussion themes.
| Theme | Character |
|---|---|
| Recovery milestones and peer support | Dominant: sobriety counts, encouragement, “one day at a time” |
| Dignity and empowerment | Recurring: the approach treats people as capable, not as patients |
| Call-to-action response | 2,270 unique “Together We Rise” instances (~4.5% of comments) |
| Skepticism | A minority: addiction-as-choice arguments, met with pushback in threads |
| Belief in scalability | Repeated: viewers see the model as expandable and want a role in it |
Method and limits
The retained analysis documents the corpus size, the normalized call-to-action count, and the qualitative theme map. It does not preserve a reproducible extraction, deduplication, or coding log. I therefore do not present percentage-level sentiment estimates or compare the call-to-action share with a platform engagement benchmark. If I rebuilt it, I would preserve the source data, normalization rules, coding schema, and an auditable analysis script.
What it established
That a mainstream entertainment audience met a recovery-community story with participation rather than distance, and that the participation was measurable: 2,270 people typed the call to action back into the comments. What I would rebuild is the evidence trail underneath it, so the theme map could be defended line by line instead of summarized.