You can use this excellent bookmarklet that I snapped from here a good handful of months ago—
javascript:function hn_bc(r){if(r.hits>0){window.location=%22http://news.ycombinator.com/item?id=%22+r.results[0].item.id;}else{if(confirm(%22This URL is not yet added to Hacker News. Would you like to submit it?%22)){window.location=%22http://news.ycombinator.com/submitlink?u=%22+encodeURIComponent(document.location)+%22&t=%22+encodeURIComponent(document.title);}}}hn_b=document.createElement(%22script%22);hn_b.setAttribute(%22src%22, %22http://api.thriftdb.com/api.hnsearch.com/items/_search?callback=hn_bc&filter[fields][url][]=%22+escape(document.location));document.getElementsByTagName(%22head%22)[0].appendChild(hn_b);
It submits the article to HN, but if it's already been submitted, it redirects you to the relevant discussion.
If I recall from the original article, they didn't know what to put there yet, it was just undesignated space, and they jokingly labeled it "tennis courts".
Neat idea. At a glance this was the year of Git. Appears 13 times. Anyone with some spare minutes wanna do a quick top-word-distribution on the titles? I'd be curious what else trended as popular.
It would be cool if it had a link to the HN comments that go along with each article. I find a lot of value in the discussion that accompanies each story most of the time.
Note to self: this could be a data mining web app if encumbered with proper algorithms
earlyriser: would you mind sharing what is the logic when deciding which article is "the most" popular? is it a simple time snapshot or something more intricate? have you considered using Instapaper API?
I'm collecting more infos that what is available at this moment, but I need to find time to implement it. In which way are you suggesting Instapaper? Do they have something like the most popular? I quickly checked their API but I couldn't not find anything for rrrewind.
Instapaper is for bookmarking and reading. It strips unnecessary clutter. You provide links to interesting stories - one might want to read them in a more readable format or send it to Instapaper and read it later on a tablet.
Here is my rumble: I'm thinking about an algorithm that would work like singnal-to-noise ratio detector. This requires a lot download bandwidth. It means counting how fast people like, +1, or any other on the internet (techcrunch, etc). Simply, replicating similar logic that HN uses for moving articles from newest page to the front page just for the top 10-20 most popular tech websites (techcrunch, gizmodo, etc). Then you add nice readability features (e.g., Instapaper) and you have a business. I might have a prototype next year but it seems that you have infrastructure that sets you ahead.
I just want to provide links to the stories. No content because I'm not sure it's ok with Copyright laws and honestly it's just a pet project. Go for it, rrrewind will remain in this form basically, maybe a mobile version and that's all.
I'm happy with this project, it gives me the content I missed and I get in contact with interesting people.
Hey, what tool did you use to do that? I kinda want to do the same for my site but I am in a bad terms with photoshop. Maybe you can send me the psd file, please?
28 comments
[ 6.1 ms ] story [ 75.0 ms ] threadEvery night rrrewind takes a snapshot of the top stories on HN. This 2011 recap is taking the top story from each day.
Good work :)
http://cdespinosa.posterous.com/plan
http://cdespinosa.posterous.com/plan
Nothing stands out. Google gets 26 hits, YC gets 14, Apple gets 13 (between 'apple' and 'apples'), HN gets 10.
I am moderately surprised that github (9) gets more hits than facebook or twitter (7).
The other surprising one was __, but that turns out to be three hits in one title after stripping punctuation. (http://adamcecc.blogspot.com/2011/01/javascript.html)
15 : yc
12 : apple
10 : hn
9 : github
9 : twitter
8 : hacker
8 : jobs
8 : news
7 : steve
7 : facebook
6 : amazon
6 : gmail
6 : developers
6 : startup
5 : sopa
4 : tracking
4 : launches
earlyriser: would you mind sharing what is the logic when deciding which article is "the most" popular? is it a simple time snapshot or something more intricate? have you considered using Instapaper API?
I'm collecting more infos that what is available at this moment, but I need to find time to implement it. In which way are you suggesting Instapaper? Do they have something like the most popular? I quickly checked their API but I couldn't not find anything for rrrewind.
Here is my rumble: I'm thinking about an algorithm that would work like singnal-to-noise ratio detector. This requires a lot download bandwidth. It means counting how fast people like, +1, or any other on the internet (techcrunch, etc). Simply, replicating similar logic that HN uses for moving articles from newest page to the front page just for the top 10-20 most popular tech websites (techcrunch, gizmodo, etc). Then you add nice readability features (e.g., Instapaper) and you have a business. I might have a prototype next year but it seems that you have infrastructure that sets you ahead.
I'm happy with this project, it gives me the content I missed and I get in contact with interesting people.
I created a better one (based on pg's essay) a while back: http://www.tagxedo.com/shop/y-combinator