I think aggregators like SkimFeed miss an important point, often made on HN: for a lot of people, including me, a lot of the value of HN is in the comments. In fact, going to the extreme, some posts have little learnable content other than TIL. First example that comes to mind is a post I recently upvoted: Reply of the Zaporozhian Cossacks (https://news.ycombinator.com/item?id=19946989) which had a small number of information-rich comments. Or there are pots where the content is obvious from the title, where I go directly to comments to see people's assessment, e.g. Federated Learning (https://news.ycombinator.com/item?id=19944510). On average I would say value of comments to post is 80 to 20 percent for me.
So, rather than tools for submission-based skimming/alerts, I'd like to see advanced tools based on comments: Some ideas:
* Number of comments divided by submission points is a rough measure of contentious topics in the HN community, esp. if this is > 1. Recent example: https://news.ycombinator.com/item?id=19970544. Sort front page by this score. Another obvious measure would be the number of grayed out and flagged comments.
* Identify comments leading to discussions and highlight them. Since comment scores are hidden this has to be done trough analysis of replies (maybe keywords "good reply" or number of replies).
* Identify comments that are informational, simple measure would be to count the number of links; harder to do would be to analyze the "factfullness".
Just some random thoughts.
P.S. I offer myself as a cautionary example of getting too much into HN: This is the first site I skim on my phone when I get up (to get awake, you know) and I easily spend more than an hour every day (who am I kidding, more like two hours). This is idiotic! Don't let your idea debt (https://news.ycombinator.com/item?id=11027684) accumulate.
Sometimes I do not even read the article at all. Either I read a few comments, and if it seems interesting I go to read the article. And sometime I just read all the comments without even putting an eye on the article. So yes, I strongly agree. HN value is in the comments.
PS: I just notice I did it again here... replying to a comment without having seen the article. I know in general it is better to have read the article before commenting, for sure for top levels comments at least, but in this case my answer is independent of the original content.
Conventional wisdom says filter bubbles are bad because they hide alternative viewpoints.
But after I've understood and incorporated alternate views and I'm ready to build, then I want to discuss with like-minded people to refine the ideas and take action.
When I'm done with discovery and I'm ready to act, I don't want to keep fighting trolls and pedants, re-litigating stale arguments, weak signal lost in the noise.
Well a bubble is an imagined abstraction. Like most abstractions, it doesn't actually exist. Its just a way to simplify things. Also, there isn't a clear definition of it either, making things even more muddy.
>HN, while being above average, collectively gets many, many things wrong.
That is to be expected. I mean we have programmers opining on quantum physics, bio-chemistry, economics, sociology, and whatever else hits the front page. I don't know of an online community that restricts their opinions to their own domains.
> Well a bubble is an imagined abstraction. Like most abstractions, it doesn't actually exist. Its just a way to simplify things. Also, there isn't a clear definition of it either, making things even more muddy.
The fact that humans came up with a fuzzy concept to mentally model real-life effects doesn't diminish the existence of those effects. Events occur independently of what names and categories we give them.
For example, hordes of Twitter users have self-selected who they follow until they're exposed to opinions that agree with their own. This is and has been happening out there, in the real world, to real people. Humans, being pattern recognizers, naturally think of this effect in terms of "bubbles" or "echo chambers." These are not defined in a strict mathematical sense, and they don't actually exist, but the phenomenon certainly does.
>These are not defined in a strict mathematical sense, and they don't actually exist, but the phenomenon certainly does.
That's my point, I'm disputing the central assertion that these phenomenon actually model reality.
>For example, hordes of Twitter users have self-selected who they follow until they're exposed to opinions that agree with their own. This is and has been happening out there, in the real world, to real people.
You can always point to people who unfollow others when exposed to world-view-contradicting opinions. But it hasn't been shown that they always do it, or do it for the same reason in every case. people can and do exhibit contradictory behavior, or have the wrong information, or are simply enjoying the drama, or are trolling, etc. The existence of these and other factors, which are just observations (not models) of human behavior, go against the nice and easy explanations of someone being in a bubble.
We like to put people inside neat little boxes with labels on them. Like you said - " Events occur independently of what names and categories we give them.".
"However, as we focused on politically-savvy users on Twitter, the reader should not infer that our observations generalize immediately to other settings, or that echo chamber effects are as pronounced for the general public."
Exactly what I said - " But it hasn't been shown that they always do it, or do it for the same reason in every case."
I don't know why you are pointing to a study that agrees with me.
I also find the comments more valuable and often reference a better version of the article so my path is:
title-->comments-->article (often a better link or summary than the original).
I'd say this is rarely the case, the exception being technical posts where alternatives, etc are discussed. Most of the content on 'hacker' 'news' are product announcement spam and tesla/bitcoin/737/facebook drama posts that continue beating the respective dead horses. The comments sections for these are filled folks having 'discussions' inspired by the article title by throwing anecdotes at each other, and armchair investigators throwing anecdotes at each other in vain attempts to argue for/against whatever they interpret the article title to mean.
Very often I find myself just visiting 'hacker' 'news' while signed out to find interesting articles to read in all the drama noise and obvious spam.
n-gate.com, while meant to be a very sarcastic take on HN, is surprisingly accurate in their descriptions.
Another website is hckrnews.com, which is an aggregate of all HN posts by time. It’s really useful if you want to capture all items, as it has a feature that shows you where left off
I browse HN via RSS aggregator; so I catch all the articles, the thing is designed for keeping track of what you've read, integrates with daily reading flow along with all the other RSS feeds. Bonus points, my RSS aggregator of choice has a nice mobile reading experience too so my browsing experience tracks seamlessly across my various platforms.
> We like to think about filter bubbles with respect to political divisions on Facebook. Users are relentlessly profiled and marketed-against there. However, they are a natural consequence of the HN algorithm too.
No way, there's just one ranking algorithm for everyone.
If you have the time, a lot of good stuff flies through without getting upvoted (enough). But this is great for me as my job is to curate such stuff for elsewhere ;-)
It lists the 10 highest-rated stories each day. I added the RSS feed to my news reader so I can see the biggest items even if I don't happen to read HN that day.
I'm confused about the mention of filter bubbles in this context. Generally, they're only bad when they're highly customized to what the individual user wants to see (because it will heavily bias toward their current beliefs).
Maybe it's the negative connotation I have to them due to Facebook so I'm wondering why this is mentioned here. I would expect the "proper" use of a filter bubble to be the application mentioned: not tailored to each individual user but rather highlighting what the entire community will find relevant, in this case based presumable on votes (though we wouldn't know if clicks are also a factor given the proprietary algorithm).
Of course, I suppose an entire community like HN could develop a macro bubble but one might presume an entire community should already have diverse perspectives which could keep it more balanced.
The way I usually learn about interesting threads (which I mostly like to read after a while so they have enough comments) is the HackerNewsletter[0].
Also (shameless plug), I built AskHN Digest[1], a weekly recap of the top threads of AskHN with their top comments, to make sure I don't miss any good content from the section. Many times the comments there have been insightful and made it worth visiting the thread after a while, when most people had the chance to comment on it.
Usually just skim the comments to gather insight as quickly as possible, if there seems to be a strong signal with depth, I'll add the HN page to Pocket (https://getpocket.com) and check back later when I clear through all the backlog of interesting things
HN has replaced Reddit for me. I'm still reading Slashdot, two decades later, it usually just dupes HN.
Also Lobsters (https://lobste.rs) has some decent content, similar position in that it often dupes HN, but interesting regardless
I use an old FF version running greasemonkey just to browse HN. My GM script concats two pages of posts, filters out any posts that have less votes than x/hr since being posted, and highlights ones that have a list of keywords I'm interested in.
I love FF, but it's a constantly shifting target esp wrt greasemonkey! I gave up trying to convert my old scripts.
Sounds like a lot of work. There's a Telegram channel that posts all links when they hit a score of 50, so you don't need to filter and you know what you've read and what you haven't (@news_ycombinator on Telegram).
It's basically the same idea as the good old Google Reader.
I wrote a script which opens a bunch of random HN links in new tabs. In firefox you have to over-ride the default amount of tabs you can open and change it to something like 9999. I once shared the script on HN under a different account, and it got no interest at all. The idea behind the script is that it presents random articles, so there is no bias behind the webpage you are reading. I use the script all the time and it's great to be presented with articles you otherwise would not have clicked. It's not hard to write such a script, but it gets trickier when you start to add filters to it. So for example, you may want to omit opening links with 'Soylent', 'Drone' or 'Trump' in the title.
So, rather than tools for submission-based skimming/alerts, I'd like to see advanced tools based on comments: Some ideas:
* Number of comments divided by submission points is a rough measure of contentious topics in the HN community, esp. if this is > 1. Recent example: https://news.ycombinator.com/item?id=19970544. Sort front page by this score. Another obvious measure would be the number of grayed out and flagged comments.
* Identify comments leading to discussions and highlight them. Since comment scores are hidden this has to be done trough analysis of replies (maybe keywords "good reply" or number of replies).
* Identify comments that are informational, simple measure would be to count the number of links; harder to do would be to analyze the "factfullness".
Just some random thoughts.
P.S. I offer myself as a cautionary example of getting too much into HN: This is the first site I skim on my phone when I get up (to get awake, you know) and I easily spend more than an hour every day (who am I kidding, more like two hours). This is idiotic! Don't let your idea debt (https://news.ycombinator.com/item?id=11027684) accumulate.