Hot or Not? Gays React to Thirst Traps

Two gay men based in Japan — Andrew and Meng — react together to a series of social media thirst traps using a 'Do, Marry, Kill' (later Kiss) framework. The main throughline is not the ratings themselves but the conversation they spark: about age preferences, the performative nature of thirst traps, the cultural valuation of youth, and the emotional complexity of consuming idealized images of attractive men. The video opens with Meng recounting being stood up on a date, and closes with a lighthearted detour into a cute animal video.

• ·Meng opens the video by sharing he was stood up on a date in Shinjuku — the person confirmed, then went silent for 30 minutes without explanation.
• ·Andrew recounts a similar experience in Shibuya years earlier, where someone messaged right up to the meeting time and then vanished, later contacting him a year afterward as if nothing happened.
• ·Both hosts note that last-minute cancellations and ghosting are common occurrences on dating apps in Japan.
• ·The main segment involves reacting to a series of thirst traps — short, performative videos of physically attractive men — and categorizing each as 'Do,' 'Marry,' or 'Kill' (a 'Kiss' option is added partway through).
• ·Andrew's dominant reaction to most clips is that the men are too young, describing several as looking like 'children' or 'college students.'
• ·Meng is more willing to acknowledge physical attraction to the younger subjects but agrees they would not be compatible relationship partners due to different life stages.
• ·Andrew criticizes the over-performative quality of many thirst traps — the deliberate camera faces, choreographed moves, and forced poses — saying it actively turns him off.
• ·Both hosts note that viewing thirst traps in a social setting changes the experience; content that might feel compelling alone feels flat or awkward when watched together.
• ·Andrew shares that certain thirst traps make him feel sad or envious — a reaction he describes as wanting to 'be' the person rather than 'be with' them.
• ·He distinguishes this from how straight men might consume images of women, suggesting gay men experience a layered dynamic of desire and comparison that straight men typically would not.
• ·The hosts discuss the general cultural valuation of youth as a marker of attractiveness, noting this exists in both Asian and Western cultures.
• ·Andrew argues that at a certain point, extreme youth becomes a turn-off rather than a draw — he finds wisdom, life experience, and even physical signs of aging (like crow's feet) can be attractive.
• ·The hosts note that men in general, and gay men in particular with archetypes like the 'Daddy' or 'salt and pepper' aesthetic, have somewhat more cultural permission to age attractively than women do.
• ·Andrew recounts that at 18 he found a 31-year-old pursuing him 'pervy,' but now at 34, he considers a 34–24 age gap acceptable — though likely to face life-stage friction.
• ·Meng expresses mild discomfort at the idea of a 30-something man being sexually attracted to a college-aged person, while Andrew pushes back that 24-year-olds are adults.
• ·One of the men in the clips is identified by a viewer comment as a known OnlyFans creator; the hosts react to his content as more acceptable partly because it is less performative.
• ·When Andrew switches to his own phone to find examples more aligned with his type — older, more mature men — both hosts react enthusiastically, finding more overlap in their preferences.
• ·The hosts reflect on their differing but partially overlapping types: Andrew gravitates toward mature, experienced-looking men; Meng shares more attraction to youthful, nerdy aesthetics.
• ·The video ends by showing a clip of a small white animal (later identified as an ermine) gliding over snow, which both hosts describe as genuinely mood-lifting compared to the thirst trap content.
• ·The hosts invite viewers to send in thirst traps or suggestions for more reaction content in future videos.

Andrew and Meng open with Andrew being stood up on a date in Shinjuku, then rate a series of thirst-trap videos using a Do/Marry/Kill/Kiss format, disagreeing almost immediately on every subject. The rating game gradually dissolves into a sustained conversation about age gaps, the psychology of jealousy versus desire, Asian beauty standards, and Andrew's admission that certain thirst traps make him feel sad rather than aroused. The video ends not with a human thirst trap but with both hosts visibly more delighted by footage of an ermine in the snow than by anything they rated.

How this video's like-and-comment rate compares to this channel's running average.

Opening 15 seconds — the bit that decides whether a viewer keeps watching.

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[0:00] Oh! [0:03] Do you actually want to date younger guys? [0:05] Wait, is he not your type? [0:06] But it's not doing anything for me [0:08] Really? [0:09] He's not doing anything for me [0:10] We learned a lot about each other! [0:13] Hi Tokyo Tops!

The title frames the video as a simple rating game, but comments reveal the real draw was the philosophical debate about age cutoffs, the hosts' divergent types, and Andrew's admission that thirst traps make him feel sad. The most-liked comments ignore the rating format entirely and respond to the emotional substance.

153 comments analysed and clustered into themes.

How the audience feels — a Net Sentiment mood score, how split the room is, and an early churn signal. All from the comments, not YouTube analytics.

Net Sentiment Score over 135 analysed comments; headline adjusted toward the channel norm (Bayesian, C=20). Polarization = normalised entropy. Comment-derived — not YouTube analytics.

Who actually showed up in the comments — psychographic, topical and language mix. Computed deterministically from 135 labeled root comments.

YouTube’s 2025 discovery shift now weights satisfaction signals — comment sentiment, tone, and depth. We can’t see the model, but we can estimate its inputs. Directional only.

Key transcript moments — tap a timestamp to jump to that point in the video.

Each comment theme mapped to the transcript moment that sparked it.

Severity × frequency — ranked. Each point has an evidence quote and a concrete before/after suggestion.

What a brand or agency would see evaluating this video — which sponsors to pitch, why, what to charge, and what's safe.

No one asks for product links unprompted, so this isn't a transactional shopping audience — but the trust signal is unusually strong: comments like 'watching y'all always lifts my spirit up' (#15), 'feels like a safe space' (#86) and a steady stream of 'I love u guys' (#72) show deep parasocial loyalty, and at least three commenters announce upcoming Tokyo trips (#41, #77 'my third trip', #80). That combination — warm trust plus concrete travel intent — means a genuine host-read will land, but this audience will punish anything that feels fake: the entire video is them mocking 'performative' guys who are 'trying too hard' (10:23, comments #4, #60, #79), so a polished scripted ad would backfire.

Algorithm Signal is a proxy. YouTube’s satisfaction scores aren’t public. Directional, not predictive.

Unanswered questions and explicit requests from the comment thread — fuel for the next upload.

Three video ideas pulled directly from what the comments asked for.

Concrete, testable changes for the next upload. Each cites a timestamp, a comment quote, or a metric — and names what to watch.

Who to reply to first — ranked by impact, with a ready-to-send draft in your voice.

Shareable social-proof quotes — ready for thumbnails, community posts, or a sponsor deck.

Moments worth cutting into Shorts — each with a title and a ready hook line. Timestamps link to the video.

Verbatim — the 5 most representative comments from the thread.

Top reply-magnet comments — where the real debate happened. 17 replies across 15 roots · max chain 3 deep · creator replied to 5%

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