Stories removed from the Hacker News Front Page, updated in real time (2024)

HN Moderation, Flags, and Transparency

• Several comments describe HN moderation as a mix of automation (flamewar detection, rate-limiting) and user flags, with limited human capacity for hot threads.
• Some see the current system as vulnerable to brigading, marketing, and state/ideological campaigns; others believe a “silent majority” keeps spam and politics down.
• There is confusion over “flag” vs “hide”: some use flag as a mega-downvote to remove topics they dislike, while others argue flagging should be for spam/abuse and “hide” for personal filtering.
• Requests recur for more transparency: seeing flag counts, who flagged, when flags are disabled, and clearer separation of “editorial” actions (front-page shaping) from comment moderation.
• Disagreement exists over “hidden restrictions”: some insist there are none; others mention rate limits, disabled voting, and past shadow-banning mechanisms.

Debate over Politics on HN

• One side wants HN as a respite from ubiquitous political ragebait, arguing politics is a “mind-killer” and reliably degrades threads into flamewars.
• The other side argues “everything is political” in practice (tech regulation, surveillance, immigration, war, labor, billionaires, Musk/X, etc.), and banning such topics entrenches the status quo.
• Many note a paradox: military or immigration-related technology is allowed, but discussion of impacts, power, and victims is often flagged as “too political.”
• Some suggest that “non-political” often means “don’t challenge my side” and that avoiding politics itself is a political choice; others reject this as bad-faith framing.
• Several commenters would like a separate, well-moderated “HN for politics,” but doubt it’s realistically maintainable.

AI/LLM Fatigue and Filtering Ideas

• Many users are tired of AI/LLM stories and branding (“AI monitors,” endless benchmarks, repetitive hype/doom posts) even while actively using the tools.
• Others enjoy substantive AI content but dislike endless low-evidence productivity claims and rehashed pro/anti talking points.
• Comparisons are drawn to past naming fads (e-, i-, net-, cloud-, crypto-), suggesting the current AI suffix craze is cyclical.
• Multiple user-side solutions are discussed: RSS filters, browser extensions, bookmarklets, and keyword-based alternate frontends; there’s debate over whether LLMs vs classic Bayesian filters are appropriate for content filtering.

Perceived Bias, Censorship, and HN’s Evolution

• Some see systematic flagging of posts critical of specific right-wing figures/causes (e.g., Musk, ICE, DOGE, Grok) while tech-only coverage of the same entities remains.
• Others counter that many political submissions skew from one side, or that low-quality culture-war threads are rightly suppressed.
• There is nostalgia and disagreement over how political HN “used to be,” but broad agreement that repetitive, low-signal threads (including about AI) are increasingly culled.
• A few commenters appreciate the Git-based GitHub feed as a clever, “hacky” way to track removals and make moderation effects more observable.