The hairball was much worse before. I used a lot of techniques from this paper [1] to make it look decent and a bunch of other heuristics based on other papers to make it look informative.
I'd give it a shot to make node embeddings with Node2Vec [1] and then reduce them to 2D with UMAP [2]. I think it could help breaking apart the hairball, assuming you have a nice clustered structure.
This is very cool but also not accurate, at least for jakeseliger.com. Henryn.ca lists 0 links from jakeseliger.com to nytimes.com, reason.com, and numerous others that simple search demonstrates are linked to, for example: https://jakeseliger.com/?s=nytimes.com&submit=Search
I put up many links posts, so I probably link to an abnormally large number of sites.
Yep this is only for stuff that we've crawled, so we can't detect all of your links. Because we have limited crawling resources, we rate-limit the crawling by domain so we don't get stuck in spider traps.
The current visualization only shows the current state of the crawl, so it won't know about all of the posts.
> I scraped my favorite blogs and made a graph from the domains that each blog links to.
Nice analysis! However, I'm guessing these arent your fav blogs as there are tens of thousands of entries! How did you decide which blogs to index, did you use some central registry of blogs?
Very neat! So you wrote the graph visualization UI? I see in prior project you used cytoscape - any motivation for doing it yourself this time (vs one of the available libraries)?
Yeah I used cytoscape before but it didn't have the full customization that I wanted. Besides the performance issues, there were some problems I couldn't have solved without a custom renderer
- if many lines overlap, how should their colors blend?
- how to render circles so that they look nice both zoomed in / out
- how to avoid it looking like a hairball graph [1]
The nice thing about a personal project is that I can do whatever I like with no constraints, so I built one that's suited for this project and fits my tastes.
Reminds me of the intern project I worked on at Google back in 2008.
My mentor at the time had a traceroute dataset of the Internet and wanted to render it on top of Google Maps. I implemented a MapReduce algorithm that geolocated the data points and then produced Google Maps tiles at various zoom levels to show how the Internet was connected. It was pretty cool to visualize how the data flowed throughout the world and to be able to "dig deeper" by zooming into the mess of connections. Very similar to what this project does!
The project didn't go anywhere but it was a cool fun experiment and a great learning opportunity for me (S2 geometry is... well, weird, but touching MapReduce and Bigtable were invaluable exercises for my later tenure at the company). Those were very different times. I don't think you would be able to pursue such a "useless" project as an intern at Google these days.
IIRC we used the LGL algorithm (https://lgl.sourceforge.net/) while pinning any nodes we could get geolocations for, giving a nice hybrid geo/topo layout
I don't remember exactly how we got the geolocations, but often network routers have 3-letter airport codes in their DNS names, so maybe that? We may also have had a lookup table in el googz somewhere
Definitely a project whose time should again come! ;)
Oh that’s right! We had to use LGL in addition to geolocation to lay out points without data. And yeah, the geolocation came from some internal service.
Well, the results are quite strange. Mine ( ploum.net ) is said to have 7 links to youdoblog. (which is false, there’s only one link to that website in all my 900 blog posts).
This is a neat idea - however, I think the graphical view of the blog graph trades "coolness" for "utility".
Have you thought of a front end that is basically just text/plain HTML (in normal size) + navigation links to explore the blogs in one frame, and the currently chosen blog in another frame? That way, you could look at the blogs while travelling your crawl graph, a kind of "blog explorer".
Reminds me of my friend's visualisation of tracks on the popular London station NTS https://www.barneyhill.com/pages/nts-tracklists/. Turns out a lot of cool artists like the same tracks... ;)
Yep this is only for stuff that we've crawled, so we can't detect all of your links. Because we have limited crawling resources, we rate-limit the crawling by domain so we don't get stuck in spider traps.
The current visualization only shows the current state of the crawl, so it won't know about all of the posts.
Awesome, I've always wanted to build something like that on top of YaCy just so that I could properly select new potentially interesting sites to index. (I can't rely on the auto-index unfortunately because it has no option to pre-confirm before indexing.)
This is only tangentially related, but has anyone done similar for HN comments? I'd be curious to know who responds to whom on particular topics, etc....
To get their topics? I used a basic louvain community detection algorithm, then put all the URLs into GPT with some few-shot prompting tricks to get it to output a particular topic. There's some heuristics to break up giant communities / combine small communities in there too.
Interesting, I was curious what I would be categorized as and it's "Whistleblowing and Leaks", which I do suppose is what my content has lately been to some extent but it was funny to see that written out.
My question for you is how can I see what sites link to me, as opposed to what sites I link to?
https://cambridge-intelligence.com/how-to-fix-hairballs/
[1] https://jgaa.info/accepted/2015/NocajOrtmannBrandes2015.19.2...
[1] https://pytorch-geometric.readthedocs.io/en/latest/generated... [2] https://umap-learn.readthedocs.io/en/latest/
https://aviz.fr/~bbach/confluentgraphs/
Your visualisation tool may require it in a specific format, but it still about properties of your data.
You can see clusters forming of websites that talk about similar topics, like crypto, rationality, Canada, India, and even postgres!
The visualization was made entirely in webgl with some neat optimizations to render that many lines and circles.
I put up many links posts, so I probably link to an abnormally large number of sites.
The current visualization only shows the current state of the crawl, so it won't know about all of the posts.
Nice analysis! However, I'm guessing these arent your fav blogs as there are tens of thousands of entries! How did you decide which blogs to index, did you use some central registry of blogs?
The nice thing about a personal project is that I can do whatever I like with no constraints, so I built one that's suited for this project and fits my tastes.
[1] https://cambridge-intelligence.com/how-to-fix-hairballs/
One nice feature that would be helpful is the ability to preview the blog.
My mentor at the time had a traceroute dataset of the Internet and wanted to render it on top of Google Maps. I implemented a MapReduce algorithm that geolocated the data points and then produced Google Maps tiles at various zoom levels to show how the Internet was connected. It was pretty cool to visualize how the data flowed throughout the world and to be able to "dig deeper" by zooming into the mess of connections. Very similar to what this project does!
The project didn't go anywhere but it was a cool fun experiment and a great learning opportunity for me (S2 geometry is... well, weird, but touching MapReduce and Bigtable were invaluable exercises for my later tenure at the company). Those were very different times. I don't think you would be able to pursue such a "useless" project as an intern at Google these days.
Dataset was something from CAIDA, like this: https://www.caida.org/catalog/datasets/ipv4_prefix_probing_d...
IIRC we used the LGL algorithm (https://lgl.sourceforge.net/) while pinning any nodes we could get geolocations for, giving a nice hybrid geo/topo layout
I don't remember exactly how we got the geolocations, but often network routers have 3-letter airport codes in their DNS names, so maybe that? We may also have had a lookup table in el googz somewhere
Definitely a project whose time should again come! ;)
Thanks for chiming in. Good times!
Have you thought of a front end that is basically just text/plain HTML (in normal size) + navigation links to explore the blogs in one frame, and the currently chosen blog in another frame? That way, you could look at the blogs while travelling your crawl graph, a kind of "blog explorer".
And I have my own internal links visualization, which might be a bit over the top (GPU recommended): https://taoofmac.com/static/graph
Yep this is only for stuff that we've crawled, so we can't detect all of your links. Because we have limited crawling resources, we rate-limit the crawling by domain so we don't get stuck in spider traps. The current visualization only shows the current state of the crawl, so it won't know about all of the posts.
adithyabalaji.com
My question for you is how can I see what sites link to me, as opposed to what sites I link to?