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@lorenzoonchain
表哥，happy sci 的善款被币安员工直接销毁了，这个事情你怎么看？就算她他不想参与，是不是也要返还给大家啊或者给社区做贡献啊？
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@cz_binanceposted on X
These reader-context are very helpful. Would be great to see X automatically apply a "AI Generate" tag on all posts that are likely AI generate. And ideally, an optional filter to not seem them at all. https://t.co/E6jxCCigGR
View original tweet on X →
Community Sentiment Analysis
Real-time analysis of public opinion and engagement
Sentiment Distribution
78% Engaged
51% Positive
27% Negative
Positive
51%
Negative
27%
Neutral
23%
Key Takeaways
What the community is saying — both sides
Supporting
1
Strong support for an "AI-generated" tag and an optional filter
many replies call it a "game changer" that would let users clean their feeds, restore trust, and reduce noise.
2
Widespread frustration with AI spam
commenters describe timelines as flooded with low‑quality "digital garbage" that drowns out real voices and even misleads vulnerable audiences.
3
Demand for automated, confidence‑based detection
people want an automatic probabilistic tag (with confidence scores) and a simple "hide AI posts" toggle rather than relying only on manual Community Notes.
4
Serious worries about false positives
many emphasize detection mistakes could wrongly flag genuine human content, so transparency about criteria and error rates is essential.
5
Calls to use AI to fight AI and improve provenance
suggestions include using models like Grok to detect synthetic media, plus watermarks or verifiable provenance to prove authorship.
6
Preference for user choice, not censorship
commenters frame tagging + filtering as a UX control—letting readers opt out of AI content while preserving creators' freedom.
7
Platform‑level and cross‑platform ambition
numerous replies urge X and other networks to adopt a common standard so the problem doesn’t just migrate elsewhere.
8
Global, multilingual consensus
replies in Chinese, Vietnamese, Turkish and English echo the same points—support for labeling, concern about noise, and caution about detection accuracy.
Opposing
1
“数字泔水”
a recurring joke that frames much of the conversation as low-value, AI‑like noise and cheap memes, with many calling out “AI slop everywhere” and questioning authenticity.
2
charity controversy
(the “happy sci” donations), with calls for accountability and one reply drawing notably high engagement (73 likes), turning the thread toward trust and governance.
3
AI
threads through the replies: people worry AI erodes creativity, produces false positives in moderation, and could become uncontrollable, while others insist AI artifacts are easily spotted.
4
Mixed in are warm, meme‑heavy reactions — greetings, praise (“Legend”), requests...
Mixed in are warm, meme‑heavy reactions — greetings, praise (“Legend”), requests for a book or new products, and playful Photoshop/meme references — keeping the tone part critical, part fan community banter.
5
Underlying all this are trust and policy concerns
accusations about platform ties and moderation decisions, plus predictions that tools to hide or remove AI footprints will become big sellers.
Top Reactions
Most popular replies, ranked by engagement
N
@NiannianCTO_BNB
Real. No AI https://t.co/dVYHqDNRzZ
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@bulkedsol
is this AI, CZ?
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@A9Less
草根文化
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@CryptoGuy_BNB
So that we can differetiate between real or fake. So hard to believe in anything nowadays. 😪
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@wenmin16
我觉得大表哥的观点非常有必要。现在对于创作的门槛越来越低了，文章可以AI写，图片视频可以AI生成，人反而成了AI的搬运工，经常分不清AI内容与真实内容。
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