Tootfinder

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 242 nodes and 6594492 edges.
Tags: Social, Offline, Unweighted, Weighted, Temporal, Metadata

Kremlin pushes for closed-door Ukraine talks, says Alaska summit understandings are foundational: https://benborges.xyz/2026/02/10/kremlin-pushes-for-closeddoor-ukraine.html

"AI is built on the collective knowledge of humankind."
No. Nononononono. It is not built on _knowledge_, it it built on _data_. And not everyone's experiences are available as data, many communities are excluded. Also: "Collective" implies some sort of collaboration and shared activity. But "AI" is just accumulation by a few powerful.
So No. It's not collective but extractive, not knowledge but data, not humankind but the hegemonic western …

Vast Ship Clusters and Speeding Tankers Point to Hormuz Jamming | Financial Post
https://financialpost.com/pmn/business-pmn/vast-ship-clusters-and-speeding-tankers-point-to-hormuz-jamming

The United States has urged its citizens to 👉leave Venezuela immediately
amid reports that ⚠️armed paramilitaries are trying to track down US citizens,
one week after the capture of the South American country’s president, Nicolšs Maduro.
In a security alert sent out on Saturday,
the state department said there were reports of armed members of pro-regime militias,
known as #colectivos

Incremental (k, z)-Clustering on Graphs
Emilio Cruciani, Sebastian Forster, Antonis Skarlatos
https://arxiv.org/abs/2602.08542 https://arxiv.org/pdf/2602.08542 https://arxiv.org/html/2602.08542
arXiv:2602.08542v1 Announce Type: new
Abstract: Given a weighted undirected graph, a number of clusters $k$, and an exponent $z$, the goal in the $(k, z)$-clustering problem on graphs is to select $k$ vertices as centers that minimize the sum of the distances raised to the power $z$ of each vertex to its closest center. In the dynamic setting, the graph is subject to adversarial edge updates, and the goal is to maintain explicitly an exact $(k, z)$-clustering solution in the induced shortest-path metric.
While efficient dynamic $k$-center approximation algorithms on graphs exist [Cruciani et al. SODA 2024], to the best of our knowledge, no prior work provides similar results for the dynamic $(k,z)$-clustering problem. As the main result of this paper, we develop a randomized incremental $(k, z)$-clustering algorithm that maintains with high probability a constant-factor approximation in a graph undergoing edge insertions with a total update time of $\tilde O(k m^{1 o(1)} k^{1 \frac{1}{\lambda}} m)$, where $\lambda \geq 1$ is an arbitrary fixed constant. Our incremental algorithm consists of two stages. In the first stage, we maintain a constant-factor bicriteria approximate solution of size $\tilde{O}(k)$ with a total update time of $m^{1 o(1)}$ over all adversarial edge insertions. This first stage is an intricate adaptation of the bicriteria approximation algorithm by Mettu and Plaxton [Machine Learning 2004] to incremental graphs. One of our key technical results is that the radii in their algorithm can be assumed to be non-decreasing while the approximation ratio remains constant, a property that may be of independent interest.
In the second stage, we maintain a constant-factor approximate $(k,z)$-clustering solution on a dynamic weighted instance induced by the bicriteria approximate solution. For this subproblem, we employ a dynamic spanner algorithm together with a static $(k,z)$-clustering algorithm.
toXiv_bot_toot

🇺🇦 Auf radioeins läuft...
Celeste:
🎵 Stop This Flame
#NowPlaying #Celeste
https://funkastik.bandcamp.com/track/celeste-stop-this-flame-funkastik-remix
https://open.spotify.com/track/1bObrsJGW0UCIGZkvnDqbe

Vast Ship Clusters and Speeding Tankers Point to Hormuz Jamming | Financial Post
https://financialpost.com/pmn/business-pmn/vast-ship-clusters-and-speeding-tankers-point-to-hormuz-jamming

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 100 nodes and 394247 edges.
Tags: Social, Offline, Unweighted, Weighted, Temporal, Metadata

sp_infectious: Art exhibit dynamic contacts (2011)
This dataset contains the daily dynamic contact networks collected during the Infectious SocioPatterns event that took place at the Science Gallery in Dublin, Ireland, during the artscience exhibition INFECTIOUS: STAY AWAY. Each file in the downloadable package contains a tab-separated list representing the active contacts during 20-second intervals of one day of data collection. Each line has the form “t i j“, where i and j are the a…