We should promote more personal indexing, rather than algorithmic indexing
However, while original sources (NASA, Reuters, bloggers, authors, scholarly journals) still write and publish (including to social media), the viral content makers, a second tier of people who write about what the original author wrote about, specializing themselves for social media, just write the grabbiest headline, and the most engaging (infuriating, polarizing, salacious) version of a piece of the original content, and when we go to our platforms, these are the content examples we see and read.
The original source's publications (posts) become almost invisible. The source becomes almost unknown as a source.
Engagement algorithms can't help this, because this is actually their purpose, which is anti-original content and -quality content.
We should design platforms and systems that allow people to index their own content again (as was the case before Web 2.0 when people manually put links to other websites, blogs, organizations, and articles on their own websites. This would make original and quality content writers become visible and indexed (even just in people's worldviews, not just indexed on the internet) and make viral content makers more invisible.
It wouldn't be total, because many people prefer the emotionality of viral content, but it would at least create an internet where there was more value available.
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[ 2.8 ms ] story [ 65.9 ms ] threadi have near 3 years worth of this at https://snafuhall.com/
doing my part.
I'm trying to downplay your comments, just its hard to start a social media company. there's a reason it's considered a tarpit idea.
Perhaps considering that may bring some creative ideas to mind for you and other hackers, other than the pessimism that seems to underlie your take here (it seems not uncommon these days).
If you get past modern spam heuristics and have 10,000 phone numbers or government IDs or whatever makes for good auth these days, then kuddos. We are all fodder for The Red Queen hypothesis. The race continues.
Inventing a fake metric like "quality" and deprioritizing "engagement" is just messaging.
I like original primary sources for some topics and secondary sources for others. For programing topics, I'm ok reading the original papers.
But for other topics ... say "civil engineering" ... I prefer a "popularizer" like Grady Hillhouse's "Practical Engineering". His 15-minute presentations are the right amount of depth for exposing me to various city infrastructure topics. I'm not going to pretend I'd be interested in reading original scholarly journals from civil engineers. I deliberately outsource that to Grady. Hardcore engineers may complain that infotainment/edutainment is "shallow learning" but people have to strategically limit themselves to "shallow" explanations of some topics so they can spend more time to deep dive into other specialized areas of interest.
The "viral content makers" serve a useful purpose in the ecosystem to satisfy varying levels of interest. Therefore, a search engine that optimized for original academic papers instead of Grady blog posts when I ask "How does a city manage stormwater runoff?" -- would not be helpful to me in most cases. I dare say a "general" search engine that didn't put academic papers on page 1 of search results would be preferred by most people.
This gets you the reliability of reading from a primary source, and the objectivity of machine summarization, with none of the capitalistic intent of the "viral human summarizers".
Also maybe hackernews should do a monthly post your blog/website just like the monthly job posts.
Comparing the atrocious search landscape of 2023 to personal indexing is to compare poorly.
Instead: those who lived through it should compare personal indexing to the golden years of altavista(.digital.com) and the extremely powerful and unpolluted results it produced and modified with boolean operators.
I never once thought that there was some utility left to be mined from the Yahoo approach to things once I switched to Altavista. I think we're only pining for personal indexing in comparison to the garbage that is Google in 2023.
A huge amount of the crap on the web is there because of Google. If you think what makes it to the top 10 is bad, you should see the crap that doesn't make it. A different search engine, with different intentions, would have to filter all that out.
If you don't believe me, try setting "showdead" on your HN profile and see all the posts the system makes [dead] before you even see them because people have some crap blog and they post nothing but links to their crap blog. I almost feel bad for those people, had they done that in 2013 they might have actually shown up in Google, today they can do that until they are blue in the face and get about zero traffic, not because Google is effective at filtering that crap out, but because they will be buried underneath all the people doing the same.
A better resource today would have to start with some radical choice such as whitelisting, if only to reduce the head-end costs of ingesting material.
It's tempting to imagine some rules like: no ads, no popups of any kind, government mandated or not, especially no cookie banners, no paywall, but even sites like Wikipedia fail at those criteria today.
> It's tempting to imagine some rules like: no ads, no popups of any kind, government mandated or not, especially no cookie banners, no paywall, but even sites like Wikipedia fail at those criteria today.
This sounds like the approach that the Marginalia (https://search.marginalia.nu/) search engine is taking. My understanding is that its algorithm favors text-heavy sites. And additions to its index are done via GitHub Pull Request so it's effectively using an approve-list (whitelist).
https://payperrun.com/%3E/search?displayParams={%22q%22:%22c...
(btw, I just launched this llm-embedding based search service that lets you check if a startup idea has already been tried/failed).
I don't know if this idea has a higher death rate than the baseline, but my guess is Google/PageRank is good enough for most use-cases, and then if you want quality sources, you can just follow them on YouTube, Twitter, Instagram, etc. Wait, maybe I shouldn't try to compete with Google?
But I think you have a good point.
There is the question of what my judgement is and the question of what your judgement is. The primary selection process (that shows me articles) is great right now, I am upvoting maybe 220 articles out of 300 in a cycle. I pick out links to post to HN and I am currently adding links to the queue faster than I am posting them which means I can definitely raise the quality of what I post but the definition of "quality" is where I get stuck. It has all sorts of factors such as a lack of annoyingness (I hate those cookie popups but there is a lot of good news behind them) but there are also articles that look really good to me at first (I like what they set out do) but then what I look at them again I realize they didn't accomplish what they set out do.
I do think votes and comments are worth something, but I also know that I could get more of both by posting clickbait articles. On one level I want to post things that are enlightening, boy I get frustrated that y'all just don't care about robotics or chemical recycling of polymers or Arduino projects. (Though my real secret ambition is to get a #1 post about sports...)
Somehow I want to pose the problem of posting to HN, Mastodon, etc. as a sequential recommendation problem which means I have to back and look at all the papers on the subject that YOShInOn has collected for me. Also I am likely to put some more work into "quality models", particularly a stacked model for predicting votes if not comments on HN articles, a broad topic model based on data from Tildes (is is sports? music? science?) and particularly sentiment models.
That last one is on my mind because I'm thinking about the emotional tone of what I post to Mastodon, some days I think I should just stick to posting flower photos because they get good engagement, but past the people who are calling everybody a "fascist" that get amplified there is a "silent majority" of people on Mastodon who try to avoid the news and other inflaming topics so I am torn between being unrelentingly positive or trying to balance out positive and negative articles to make a more appealing feed to the good people of Mastodon. It would probably be 2-3 days of labeling work to make a sentiment model but if I had to find and categorize 5000 angry toots it would kill me, but I am thinking now about grading my own posts (what the system is going to do inference on anyway) and also grading high-engagement and predicted high-engagement submissions to HN to make a model that finds high-engagement posts that aren't clickbait.
It was not Google who destroyed the Search, it was the Internet that has changed