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stared
tagoverflow
JavaScript2015–2019
stared / tagoverflow

tagoverflow

An interactive map of Stack Exchange tags for all sites.

5Distinct people
8Mentions
0Explicit recommenders
126GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

An interactive map of Stack Exchange tags for all sites.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year8 dated mentions

Observed mentions: 2015-04-05 20:00:05 UTC to 2019-05-09 14:52:07 UTC.

0123452015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 5 mentions; 1 submissions, 4 comments20152016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2019

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC514
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC101
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC202

What Hacker News says

8 sources
Author here. I did the D3.js part - the main graph and timeline. Force layout link strength was based on Pointwise Mutual Information, vide https://github.com/stared/tagoverflow. I was given the data. There is an accompanying write-up: https://culture.pl/en/article/what-makes-a-composer-polish Official project info: "Map of Polish Composers is the most comprehensive resource ever dedicated to Polish music giving users instant access to biographies, extracts from recordings and a carefully charted map providing a rich global cultural context for every artist highlighting their influences and inspirations. Map of Polish Composers is powered by Adam Mickiewicz Institute. The project is created by the Adam Mickiewicz Institute as part of the Polska Music and POLSKA 100, the international cultural programme celebrating the centenary of Poland
Read the rest
regaining independence. Financed by the Ministry of Culture and National Heritage of the Republic of Poland as part of the multi-annual programme NIEPODLEGŁA 2017–2022."
In Show HN: Map of Polish Composers
Well, if you want to do it, go for it. If I were to do so, I know more suitable methods, vide description from https://github.com/stared/tagoverflow/. Without such normalization, it won't work given that there are networking with different orders of magnitude of users. Right now don't have much time for this project, and well - I am this kind of person that has a few dozen times for idea than time, not the other way. :)
In Show HN: Tree of Reddit Sex Life
For strength of co-occurrence please use pointwise mutual information (or its function), see https://github.com/stared/tagoverflow#methods-and-tricks. I explored quite a few, and only this one gave reasonable results, including when there was a big difference in the number of counts of A and B (see: http://p.migdal.pl/tagoverflow/). Also, PMI shows up in many contexts, including word2vec. Your measure is at best hacky (no direct interpretation, leaves many small nodes without links). Otherwise, a nice work! But it would be great if visualized more interactively and aesthetically (yeah, I can be biased here).
In Visualizing relationships between Python packages

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