@netzschleuder@social.skewed.de2026-06-15 01:00:04
sp_colocation: Social co-locations (2018)
Network of colocations between peoople, based on the information on which RFID readers received information from the RFID tags. Namely, we define two individuals to be in co-presence if the same exact set of readers have received signals from both individuals during a 20s time window.
This network has 81 nodes and 150126 edges.
Tags: Social, Offline, Unweighted, Weighted, Temporal, Metadata
@jonippolito@digipres.club2026-07-14 14:31:39
@burger_jaap@mastodon.social2026-07-15 11:51:13
A great choice of image for an important topic: distributed energy resources can collectively respond very effectively to the needs of the grid
https://www.iea.org/reports/scaling-up-demand-flexibility
@aredridel@kolektiva.social2026-07-11 17:06:34
For those that don't know, I help run a large women in technology chat group on Slack. It's been going for 11 years now! (ask me for an invite if you want one and that's appropriate!)
It has deeply shaped how I think about technology, especially the social side. There is so much embodied knowledge in that community, it's amazing. And it's also such a window into how much the mainstream of technology writing is dominated by men. We talk about it differently! We're much more likely to be critical, and to be critical of the _structures_ in tech. Sometimes that comes off as kneejerk "Ugh BRIAN!" to some of the bullshit men to do women in the workplace, but also embedded underneath is an understanding of rarely-mapped power structures in the field. So much advice out there is written assuming that there is no dissent, no silent frustration, no quiet abandoning the job when the pressures are unresolved. And so much of the tech world, press and on social media alike, has no insight that this attrition even happens.
Women, collectively, though, understand it. We notice the patterns of promotions. We understand the way that if we're in our 40s, we're rather likely to have a manager who is a decade younger than we are, with no particular experience. We notice when men are lauded for spending time with their family instead of work on occasion, but women are expected to be present at all times and rarely seen positively for doing the exact same things.
And yet, any given instance is always shrouded in deniability. The pattern generally holds, but is this one my fault? Do I not measure up? Or is it sexism?
That's what these structures rob from us: we never have the clarity in feedback that it is accurate, that is us that must change. When we stick to our guns, are we being obstinate, or are we correct? That information is denied to us by sexism. It only becomes clear in aggregate, and even then it is very hard to find action to take on it except to acknowledge it and move on.
I don't think people talk about that ambiguity enough: we're always looking for the clear sexism, the man speaking over the women, the trading sexual favors for advancement, the clear pattern of pet-to-threat that so many women experience as they age or gain skill in the field. But the bulk of sexism that we experience is in the structural poisoning of feedback.
@netzschleuder@social.skewed.de2026-08-14 14:00:10
corporate_directors: Global corporate directors (2016)
Bipartite network of directors and the companies on whose boards they sit, spanning 54 countries worldwide, constructed from data collected by the Financial Times (c. Sept. 2016). Person nodes are annotated with age and gender. Company nodes are annotated with their country, sector, industry, and number of employees.
This network has 356638 nodes and 377060 edges.
Tags: Economic, Governance, Unweighted, Metadata
@netzschleuder@social.skewed.de2026-07-15 06:00:51
trec: TREC collection (2010)
A bipartite network of documents and the words they contain, extracted from NIST's Text Retrieval Conference (TREC) disks 4 and 5, from 2010. These archives contain material drawn from the Financial Times Ltd., the Congressional Record of the 103rd Congress, the Federal Register, the Foreign Broadcast Information Service, and the Los Angeles Times newspaper.
This network has 1729302 nodes and 83629405 edges.
Tags: Informational, Language, Un…
@netzschleuder@social.skewed.de2026-06-14 02:00:10
stanford_web: Webgraph (Stanford)
The web graph of Stanford University (stanford.edu), as collected in 2002. Nodes represent pages and directed edges represent hyperlinks between them.
This network has 281904 nodes and 2312497 edges.
Tags: Informational, Web graph, Unweighted
https://networks.skewed.de/net/s…
@netzschleuder@social.skewed.de2026-08-15 16:00:07
stanford_web: Webgraph (Stanford)
The web graph of Stanford University (stanford.edu), as collected in 2002. Nodes represent pages and directed edges represent hyperlinks between them.
This network has 281904 nodes and 2312497 edges.
Tags: Informational, Web graph, Unweighted
https://networks.skewed.de/net/s…
@netzschleuder@social.skewed.de2026-06-15 14:00:06
hiv_transmission: HIV transmission network (1988-2001)
A set of networks of HIV transmissions between people through sexual, needle-sharing, or social connections, based on combining 8 datasets collected from 1988 to 2001. Metadata includes test results of several diseases, as well as demographic variables such as age, ethnicity, and gender. Networks come in two flavors: egodyads and altdyads. Egodyads are the network among study-participants and their direct partners. Altdyads are the…
@netzschleuder@social.skewed.de2026-06-13 22:00:06
word_assoc: Edinburgh word associations
A network of word associations showing the count of such associations as collected from subjects, from the Edinburgh Associative Thesaurus (EAT). Each node represents a word, and a directed edge (i, j) denotes that word i was used as a stimulus to which word j was given as a response. Multiple edges are allowed.
This network has 23132 nodes and 312342 edges.
Tags: Informational, Language, Unweighted, Multigraph
