I know javascript and jQuery suffer from their popularity and utility I think in this analysis. There is also the issue of jQuery and javascript tags being used by people as synonyms. jQuery particularly is a 500 pound gorilla over all the dataset, it shows up everywhere. As I mentioned above there was a joke on SO at one point that the answer to nearly every question was jQuery with a link to the site. Apparently it wasn't a joke.
No just the post bodies (question and answers) at the moment, but we are working parsing the comments and the post history, those datasets are about 4 times the size of the posts! So there are probably a lot more URLs in there, although we will have to decide if we treat all URLs the same or if we differentiate between URLs in post bodies contained in the dump, URLs in the post history (that may have been removed from the post) and URLs in the comments. Not maybe a concern for the website, but more so for research.
Thanks. Yea i agree our initial use case was to provide an interface to the dataset and to allow us to explore what kinds of things developers were sharing on SO. For the next version we are working on new ranking metrics that will improve the discover aspect, vote:cite and view:cite are 2 we are looking at.
Thanks for the support. Yes to everything above :) We are currently mining the post history data to be able to do those kinds of time range queries. Cant wait to get that out there it should be very cool indeed, also want to allow users to search by their SO id and to filter their links by tag. (As an aside when we do mine the history we will be able to get more accuracy on which users actually posted which links rather than just the post owner.)
So these are taken from the March 2013 data dump, which includes questions going right back to the start of SO. So some of these links have been collecting citations for a few years. We only mined the actual post content on the date the dump was created, we did not mine the post history. But we are working on that right now, its a lot of data to process :)
I actually had that in an earlier version and took it out just to simplify the design but i am actually looking at this again to produce a better sorting experience. Also the number of views a post receives may be a good metric also.
Wow, that's really cool, have to admit i didn't see that before. Let me know if your interested in sharing data, we are doing a lot of research in this area and the more data the better!
Thanks for the support, really encouraged by the feedback here on Hacker News. You guys are great.
To your question, yes I am currently testing some ideas for a magic ranking system. One option is as you say a kind of random select amounts popular or trending links. Another is a smart weighted sort when filtering by multiple tags. One problem is that right now if you add jQuery to your filter, the javascript results are going to just dominate everything else.
Thanks for the heads up, will modify the parser, again if anybody knows of a good open source crawler let me know. I rolled my own very quickly but would love it if i could find a 3rd party solution. Another option i have explored is pulling in the titles and descriptions provided by search engines but currently only DuckDuckGo offers anything useful and even then its coverage of some of these low ranking programming pages isn't great. Bing offers a pay per use access to its index but the costing structure really doesn't fit with my use case.
Thanks. Re the redirects, yea I have a lot of work to do on my crawler, my current solution is hand rolled and only has limited capabilities. But if anybody knows of a good open source project let me know, i have been looking at using the common crawl but that's not a complete solution either.
Ah, you guessed my next paper :) I have done a little informal analysis on the top 10 results from linked_lists vs the top 10 for that tag used as a Google query. They are quite different, almost totally different actually. But this is not really surprising if you think of the developers curating the links posted on Stack Overflow. I know there was an attempt a few years back to build a search engine based on the SO data set, don't know what happened to that.