Tootfinder

bag_of_words: Bag of words (2008)
Five text collections in the form of bags-of-words, i.e. a bipartite document–word network. Left nodes are documents and right nodes are words. Edge weights are multiplicities. .
This network has 67963 nodes and 3710420 edges.
Tags: Informational, Text, Bipartite, Weighted, Metadata
https://…

bag_of_words: Bag of words (2008)
Five text collections in the form of bags-of-words, i.e. a bipartite document–word network. Left nodes are documents and right nodes are words. Edge weights are multiplicities. .
This network has 10336 nodes and 353160 edges.
Tags: Informational, Text, Bipartite, Weighted, Metadata
https://

About how AI tools can be useful.
#ai #coding

Claude Code Can Debug Low-level Cryptography
Surprisingly (to me) Claude Code debugged my new ML-DSA implementation faster than I would have, finding the non-obvious low-level issue that was making Verify fail.

from my link log —
Golang cryptographic assembly mutation testing.
https://words.filippo.io/assembly-mutation/
saved 2025-07-31 http…

Go Assembly Mutation Testing
Test coverage of delicate Go cryptographic assembly through a new mutation testing framework.

wiki_article_words: Wikipedia article-words (en) (2010)
A bipartite network of English Wikipedia articles and the words they contain. The edge weight gives the number of times a word appeared in the connected article.
This network has 276739 nodes and 2941902 edges.
Tags: Informational, Language, Weighted
https://

🇺🇦 #NowPlaying on KEXP's #DriveTime
Big Thief:
🎵 Words
#BigThief
https://bigchiefromero.bandcamp.com/track/three-words
https://open.spotify.com/track/2Cxs2cLG7HoXfcAlw67yIy

Beyond Words: Interjection Classification for Improved Human-Computer Interaction
Yaniv Goren, Yuval Cohen, Alexander Apartsin, Yehudit Aperstein
https://arxiv.org/abs/2509.03181

Beyond Words: Interjection Classification for Improved Human-Computer Interaction
In the realm of human-computer interaction, fostering a natural dialogue between humans and machines is paramount. A key, often overlooked, component of this dialogue is the use of interjections such as "mmm" and "hmm". Despite their frequent use to express agreement, hesitation, or requests for information, these interjections are typically dismissed as "non-words" by Automatic Speech Recognition (ASR) engines. Addressing this gap, we introduce a novel task dedicated to interjection classifica…

The three words you can whisper into the ear of any support AI chatbot to get their attention
credit card chargeback

Folks, if you see a link to Gaza Verified (gaza-verified.org) on a profile, make sure that the link has the verification badge (in the apps) or is green with a check mark (on the web app).
So, in other words, please verify that the link is actually verified.
More info on how verification works on Mastodon: https://joinmastodon.org/ve…

Verification
Learn how to get verified on Mastodon

Maxx Crosby Sends Strong Words After Raiders Lose to Jaguars https://heavy.com/sports/nfl/las-vegas-raiders/maxx-crosby-strong-words-lose-jaguars/?adt_ei=[email]

@… Thank you for your kind words! I'll pass them along to the team.

Saleh rues 'wrong choice of words' in Coen spat https://www.espn.com/mlb/story/_/id/46442241/49ers-saleh-admits-used-better-words-jaguars-coen

Bridging Thoughts and Words: Graph-Based Intent-Semantic Joint Learning for Fake News Detection
Zhengjia Wang, Qiang Sheng, Danding Wang, Beizhe Hu, Juan Cao
https://arxiv.org/abs/2509.01660

Bridging Thoughts and Words: Graph-Based Intent-Semantic Joint Learning for Fake News Detection
Fake news detection is an important and challenging task for defending online information integrity. Existing state-of-the-art approaches typically extract news semantic clues, such as writing patterns that include emotional words, stylistic features, etc. However, detectors tuned solely to such semantic clues can easily fall into surface detection patterns, which can shift rapidly in dynamic environments, leading to limited performance in the evolving news landscape. To address this issue, thi…

Sources at CBS News say newsroom morale is extremely low ahead of Bari Weiss' imminent arrival, and employees worry about her lack of experience as layoffs loom (Justin Baragona/The Independent)
https://www.independent.co.uk/news/world/a

‘It’s not a good place right now’: CBS News staffers are ‘literally freaking out’ about Bari Weiss taking over newsroom
EXCLUSIVE: ‘People are using words like depressing and doomsday – feels like some sort of doomsday,’ one source told The Independent about the mood inside CBS News right now.

OF COURSE!
LLMs do not have any knowledge They only have words. When "introspecting" they are actually just word-salading that like they do everything else. They can't SAY that so they make up plausible-seeming explanations.
BECAUSE THAT IS ALL THEY DO, EVER. https://mastodon.social/@arstechni…

Ars Technica (@arstechnica@mastodon.social)
Attached: 1 image LLMs show a “highly unreliable” capacity to describe their own internal processes Anthropic finds some LLM "self-awareness," but "failures of introspection remain the norm." https://arstechnica.com/ai/2025/11/llms-show-a-highly-unreliable-capacity-to-describe-their-own-internal-processes/?utm_brand=arstechnica&utm_social-type=owned&utm_source=mastodon&utm_medium=social

After some time, I’ve managed to clarify my reasons for not wanting to use Gen AI in my development toolset down to two words:
“Self respect”
#genai #ai

I solved today's #TiledWords puzzle!
🌙 “Night”
🕒 5 minutes, 13 seconds
💡 0/3 reveals used
https://tiledwords.com/puzzles/2025-11-03

Tiled Words
A daily word puzzle with a twist

Starter words did most of it today. #Wordle
Wordle 1 538 4/6
⬛⬛⬛🟩🟩
⬛⬛🟩⬛⬛
⬛⬛🟨⬛⬛
🟩🟩🟩🟩🟩

"This is all wrong. I shouldn't be up here. I should be back in school on the other side of the ocean. Yet you all come to us young people for hope. How dare you! You have stolen my dreams and my childhood with your empty words. And yet I'm one of the lucky ones. People are suffering. People are dying. Entire ecosystems are collapsing. We are in the beginning of a mass extinction, and all you can talk about is money and fairy tales of eternal economic growth. How dare you!"…

RE: https://theatl.social/@upstreamism/115312125311689822
In other words, BlueSky has shown it desires to be another Nazi bar.
It's up to its users now to decide if they want to stay in the Nazi bar.

bsdconfig startup
― it's sometimes easier to remember those two words, than to consult date(1).
For the umpteen VirtualBox guests and snapshots where I carelessly, or intentionally, omitted both ntp options.
<https://man.freebsd.org/cgi/man.cgi?qu

yahoo_ads: Yahoo! advertisement words
A network of words extracted from phrases on which advertisers bid, in Yahoo! advertisements. A node is a word and a directed edge (i, j) denotes word i comes after the word j.
This network has 653260 nodes and 2931708 edges.
Tags: Informational, Language, Unweighted
https://

Shape and word parts combine linearly in the Bouba–Kiki effect https://link.springer.com/article/10.3758/s13414-025-03151-1

Shape and word parts combine linearly in the Bouba–Kiki effect - Attention, Perception, & Psychophysics
Languages have evolved in part due to cross-modal associations between shape and sound. A famous example is the Bouba–Kiki effect, wherein humans associate words like bouba/kiki to round/angular shapes. How does the Bouba–Kiki effect work for natural words and shapes that contain a mixture of features? If the effect is holistic, the effect for a composite stimulus would not be explainable using the parts. If the effect is compositional, it will be. Here we provide evidence for the latter po…

I have no words for this insanity. #TeamBugs
via @…
https://

Why Stop at Words? Unveiling the Bigger Picture through Line-Level OCR
Shashank Vempati, Nishit Anand, Gaurav Talebailkar, Arpan Garai, Chetan Arora
https://arxiv.org/abs/2508.21693

Why Stop at Words? Unveiling the Bigger Picture through Line-Level OCR
Conventional optical character recognition (OCR) techniques segmented each character and then recognized. This made them prone to error in character segmentation, and devoid of context to exploit language models. Advances in sequence to sequence translation in last decade led to modern techniques first detecting words and then inputting one word at a time to a model to directly output full words as sequence of characters. This allowed better utilization of language models and bypass error-prone…

War of words – Russian propaganda threatens to “redraw the map” | Hate Speech: https://benborges.xyz/2025/08/27/war-of-words-russian-propaganda.html

#Wordle 1,508 4/6*
⬜⬜🟨⬜⬜ <1% of 219,576 (277)
⬜⬜⬜⬜🟨 0 of 48 (55)
🟩🟩🟩⬜⬜ 0 of 0 (4)
🟩🟩🟩🟩🟩
WordleBot
Skill 84/99
Luck 42/99
Curious how many words were left starting with those 3 letters after my 3rd guess...bot says 4.

MERCER ISLAND SCHOOL BOARD
Wow, you really do have to watch the downballot races. Mercer Island School Board has two (2) candidates (O'Callahan is and Gaspar) that are *both* software CTOs touting their "AI" credentials. Gaspar explicitly wants "free AI classes".
Here's a hint: The only "AI classes" that kids need are ones that teach them how to TURN ALL OF THAT SHIT OFF, and learn to think and write in their own words, not Chat-GPT'…

On two-toned tilings and $(m,n)$-words
Henri M\"uhle
https://arxiv.org/abs/2510.00226 https://arxiv.org/pdf/2510.00226

On two-toned tilings and $(m,n)$-words
In this article, we describe an explicit bijection between the set of $(m,n)$-words as defined by Pilaud and Poliakova and the set of of two-toned tilings of a strip of length $m+n$.

Geno Smith Has Strong Words for Jakobi Meyers After Raiders Trade https://heavy.com/sports/nfl/las-vegas-raiders/jakobi-meyers-trade-geno-smith/?adt_ei=[email]

CeeDee Lamb candid about drops vs. Eagles https://www.dallascowboys.com/news/ceedee-lamb-candid-about-drops-vs-eagles

So, did the letter “y” form out of the letters “ij”?
Evidence:
- they would both sound “eeyy”
- in “free”, “ee” might be English substitute for “y”
- in “free”, “ij” might be English substitute for “ij”
- “ÿ” can look exactly like “ij” in cursive
#dutch #vowels

Good. This is how it’s done.
Does this mean “you should love this politician” or “you should count on this politician to save us all” or “you should get a tattoo of this politician on your buttocks?”
No.
Does it mean “the words and behavior of public figures matter” and “politicians can be useful tools of resistance” and “keep the pressure up because it’s working?”
Hell yes. https://fed.brid.gy/r/https://bsky.app/profile/did:plc:26tsf647wqnoo7umh4ywwz7a/post/3lxuwzcx4s22r

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Big Thief:
🎵 Words
#BigThief
https://bigchiefromero.bandcamp.com/track/three-words
https://open.spotify.com/track/2Cxs2cLG7HoXfcAlw67yIy

Worked with an #acting #coaching client and seeing them sink further into the material in ways neither of us anticipated was cool. The words hit them new ways, and happily they followed and built on that to hit new versions of delivery for what came next.

Meet Ziada Kassimu: a medical assistant doctor and climate activist in Tanzania working to empower women and girls through the REPower Afrika campaign. #climatechange #climatesolutions #climate

REpower Afrika: Ziada Kassimu
“Working with 350.org has been a joy, as it's not about words: it's about action. 350 takes action on moving communities away from fossil fuels, impacting their livelihoods and giving them opportunities to grow and speak for themselves”

"Donald Trump and Pete Hegseth, by their own words, hoisted themselves on their own petard.”
Trump's 'bluster' cost him in latest legal setback: law professor - Raw Story
https://www.rawstory.com/trump-bluster/

I became disillusioned with generative AI in 1995.
"Wrote some c code that read in a text file, constructed a frequency table showing how often each letter came after each letter then randomly generated words using the frequency table to determine probabilities.
If you give it a german file, it comes up with german-like words. Feed it it's own source code, and it comes out with crap, unfortunately.. I was hoping it would write some new programs for me :)"

Integers with small digits in multiple bases
Thomas F. Bloom, Ernie Croot
https://arxiv.org/abs/2509.02835 https://arxiv.org/pdf/2509.02835

Integers with small digits in multiple bases
We show that, for any $r\geq 1$, if $g_1,\ldots,g_r$ are distinct coprime integers, sufficiently large depending only on $r$, then for any $ε>0$ there are infinitely many integers $n$ such that all but $ε\log n$ of the digits of $n$ are $\leq g_i/2$ in base $g_i$ for all $1\leq i\leq r$. In other words, for any fixed large bases, there are infinitely many $n$ such that almost all of the digits of $n$ are small in all bases simultaneously. This is both a quantitative and qualitative improvemen…

Runtime Consultants
Dana Fisman, Elina Sudit
https://arxiv.org/abs/2508.01821 https://arxiv.org/pdf/2508.01821

Runtime Consultants
In this paper we introduce the notion of a runtime consultant. A runtime consultant is defined with respect to some value function on infinite words. Similar to a runtime monitor, it runs in parallel to an execution of the system and provides inputs at every step of the run. While a runtime monitor alerts when a violation occurs, the idea behind a consultant is to be pro-active and provide recommendations for which action to take next in order to avoid violation (or obtain a maximal value for q…

bag_of_words: Bag of words (2008)
Five text collections in the form of bags-of-words, i.e. a bipartite document–word network. Left nodes are documents and right nodes are words. Edge weights are multiplicities. .
This network has 10336 nodes and 353160 edges.
Tags: Informational, Text, Bipartite, Weighted, Metadata
https://

I have found that recently (over the last year or so), my iPhone auto-correct has become worse and worse.
So I turned it off a week or so ago.
After a week, I make fewer typos than the auto-correct does, and when I do, I catch them. They don’t magically happen three words back.
And it no longer auto-capitalises “apple”.

"Shit by any [...] name would smell [...] foul, and David and his friends are extremely pungent."
https://jakelazaroff.com/words/dhh-is-way-worse-than-i-thought/

Starter words did pretty well. Only missed one letter. #Wordle
Wordle 1 508 4/6
🟨🟨⬛⬛⬛
🟩🟩⬛⬛⬛
⬛⬛⬛⬛⬛
🟩🟩🟩🟩🟩

Two post updates this week (my site host is… chunking):
• https://adrianroselli.com/2024/02/techniques-to-break-words.html#Update05 adds a W3C video about text wrap:

#ShamelesslyStolenFromTumblr

On synchronized coded systems
Wolfgang Krieger
https://arxiv.org/abs/2509.04122 https://arxiv.org/pdf/2509.04122 …

On synchronized coded systems
We introduce a class of codes with overlapping code words, that we call SPO-codes. The SPO-codes are related to the Markov codes that were introduced in: G. Keller, J. Combinatorial Theory 56, (1991),pp.\ 75--83. The process of generating a coded system from a code extends to SPO-codes. We describe a family of intrinsically ergodic synchronized SPO-coded systems that is closed under topological conjugacy. We construct synchronized subshifts with salient structural features by means of SPO-codes…

Måste komma ut som en försvarade av jobbig stavning. Stavningsreformerna där stavningen anpassas till den nuvarande fonetiken hjälper bara under en kort tidsperiod (då uttalen ändras rätt snabbt) och den förstör långa perioder av språkhistoria. Lär man sig grunderna i ett par europeiska språk kan man snabbt lära sig att se på stavningen av ett ord varifrån det kommer. Det är enormt värdefullt och jag hoppas engelskan håller fast vid det.

And many of the people that support him, let me guess…white and rich? Shocking. https://mastodon.social/@jakelazaroff/115304688954799868

I'm especially interested in a few things if anyone is willing to help...
1) missing words and simple typos - My ADHD brain skips words coming out and fulls them in when reading, so it's easy for me to make mistakes and hard for me to catch them.
2) questions - I tend to work from a lot of assumed knowledge, collected from all over, and I'm really trying to make my work more accessible. I assume I'm talking about a bunch of stuff most folks don't know, but I don't know which of them come from some rabbit hole I went down and which are more common knowledge.
3) challenges - I get bored when having things explained to me so I have a tendency to keep explanations light... Which can mean I leave out a bunch of critical context or logical steps.

A friend made this piece (based on a phrase he heard someone say after dropping an order in a restaurant.) Have truer words ever been spoken? 😬😅

A note on the non-$L^1$ asymptotic completeness of the Vlasov-Maxwell system
Emile Breton
https://arxiv.org/abs/2509.04025 https://arxiv.org/pdf/2509.04025…

A note on the non-$L^1$ asymptotic completeness of the Vlasov-Maxwell system
We prove that under a generic asymptotic condition on the charge, the small data solutions to the Vlasov-Maxwell system do not verify linear scattering. In other words, we show the non-$L^1$ asymptotic completeness of the system. The proof makes use of the Lorentz invariance of the equations.

Raiders’ Pete Carroll Issues Blunt Words to Broncos’ Sean Payton https://heavy.com/sports/nfl/las-vegas-raiders/pete-carroll-blunt-broncos-sean-payton/?adt_ei=[email]

Randomized biorthogonalization through a two-sided Gram-Schmidt process
Laura Grigori, Lorenzo Piccinini, Igor Simunec
https://arxiv.org/abs/2509.04386 https://

Randomized biorthogonalization through a two-sided Gram-Schmidt process
We propose and analyze a randomized two-sided Gram-Schmidt process for the biorthogonalization of two given matrices $X, Y \in\mathbb{R}^{n\times m}$. The algorithm aims to find two matrices $Q, P \in\mathbb{R}^{n\times m}$ such that ${\rm range}(X) = {\rm range}(Q)$, ${\rm range}(Y) = {\rm range}(P)$ and $(ΩQ)^T ΩP = I$, where $Ω\in\mathbb{R}^{s \times n}$ is a sketching matrix satisfying an oblivious subspace $\varepsilon$-embedding property; in other words, the biorthogonality condition o…

Sonnet 082 - LXXXII
I grant thou wert not married to my Muse,
And therefore mayst without attaint o'erlook
The dedicated words which writers use
Of their fair subject, blessing every book.
Thou art as fair in knowledge as in hue,
Finding thy worth a limit past my praise;
And therefore art enforced to seek anew
Some fresher stamp of the time-bettering days.
And do so, love; yet when they have devis'd,
What strained touches rh…

Brian Armstrong deliberately used certain words during Coinbase's Q3 call to sway $84,000 in bets on Kalshi and Polymarket over which terms would be mentioned (Bloomberg)
https://www.bloomberg.com/news/articles/2025-10-31/…

Mr. President. Millions have put their trust in you and, as you told the nation yesterday, you have felt the providential hand of a loving God.
In the name of our God, I ask you to have mercy upon the people in our country who are scared now.
There are gay, lesbian, and transgender children in Democratic, Republican, and Independent families, some who fear for their lives.
And the people, the people who pick our crops and clean our office buildings, who labor in poultry fa…

Full Transcript of the 2025 Inauguration Prayer Service Address by the Rt. Reverend Mariann Edgar Budde, the Bishop of Washington - San Francisco Bay Times
May the words of my mouth and the meditation of all our hearts be acceptable in your sight, oh God, for you are our strength and our Redeemer. Amen. Please be seated. Again, my warm welcome to all who have gathered in this House of prayer for all people and for those who are joining […]

Call for Submissions: *SHHH! BREATHE SLOW!* – A One-Minute Horror Plays Anthology (Volume 4)
https://ift.tt/xAsghN6
updated: Wednesday, September 3, 2025 - 2:45pmfull name / name of organization: Fresh Words-An…
via Input 4 RELCFP

Towards Stable and Personalised Profiles for Lexical Alignment in Spoken Human-Agent Dialogue
Keara Schaaij, Roel Boumans, Tibor Bosse, Iris Hendrickx
https://arxiv.org/abs/2509.04104

Towards Stable and Personalised Profiles for Lexical Alignment in Spoken Human-Agent Dialogue
Lexical alignment, where speakers start to use similar words across conversation, is known to contribute to successful communication. However, its implementation in conversational agents remains underexplored, particularly considering the recent advancements in large language models (LLMs). As a first step towards enabling lexical alignment in human-agent dialogue, this study draws on strategies for personalising conversational agents and investigates the construction of stable, personalised le…

#Wordle 1,569 5/6*
🟨🟨⬜⬜⬜ <1% of 229,026 (169)
🟩🟩🟨🟨⬜ 0 of 146 (3)
🟩🟩🟩⬜🟩 0 of 0 (2)
🟩🟩🟩⬜🟩 0 of 0 (1)
🟩🟩🟩🟩🟩
WordleBot
Skill 97/99
Luck 48/99
Well after my 2nd guess I was pretty sure there were 3 words left which I'd have to try 1 by 1. And I tried them all.

bag_of_words: Bag of words (2008)
Five text collections in the form of bags-of-words, i.e. a bipartite document–word network. Left nodes are documents and right nodes are words. Edge weights are multiplicities. .
This network has 67963 nodes and 3710420 edges.
Tags: Informational, Text, Bipartite, Weighted, Metadata
https://…

Starter words did pretty well. Only missed one letter. #Wordle
Wordle 1 508 4/6
🟨🟨⬛⬛⬛
🟩🟩⬛⬛⬛
⬛⬛⬛⬛⬛
🟩🟩🟩🟩🟩

CeeDee Lamb candid about drops vs. Eagles https://www.dallascowboys.com/news/ceedee-lamb-candid-about-drops-vs-eagles

Raiders RB Ashton Jeanty Has Strong Words for Travis Hunter Ahead of NFL Debut https://heavy.com/sports/nfl/las-vegas-raiders/ashton-jeanty-travis-hunter-heisman/?adt_ei=[email]

Density Characterization with The Upper Bound of Density of Fibonacci Word
Duaa Abdullah, Jasem Hamoud
https://arxiv.org/abs/2509.00886 https://arxiv.org/p…

Density Characterization with The Upper Bound of Density of Fibonacci Word
This paper investigates the natural density and structural relationships within Fibonacci words, the density of a Fibonacci word is $\operatorname{DF}(F_k)=n/(n+m),$ where $m$ denote the number of zeros in a Fibonacci word and $n$ denote the units digit. Through analysis of these ratios and their convergence to powers of $φ$, we illustrate the intrinsic exponential growth rates characteristic of Fibonacci words. By considering the natural density concept for sets of positive integers, it is de…

Trump praised Skydance's Paramount takeover and Bari Weiss' appointment, saying it is the "greatest thing" that has happened "to a free and open and good press" (Cynthia Littleton/Variety)
https://variety.com/2025/tv/news/donal

Donald Trump Praises Skydance's Paramount Takeover and Bari Weiss
President Donald Trump had kind words for Skydance's takeover of Paramount and Bari Weiss' appointment at CBS News in his full '60 Minutes' interview.

🇺🇦 #NowPlaying on KEXP's #AstralPlane
Darker My Love:
🎵 Talking Words
#DarkerMyLove
https://digital.dangerbird.com/track/talking-words
https://open.spotify.com/track/4DS7tR5BWivVNxJ6eWcyHP

Wise words from @….
Reflecting now on how often I find myself saying “Just show up, over and over, and do some work. Don’t worry about whether it’s enough, about whether you’re going to get an A. Just show up. Do some work.”
Wanting to get really good at [software dev skill]?
Worried about passing the class?
Not sure if you’re a Real Programmer yet?
Impostor feelings?
Horrified at politics?
Wanting to saving democracy?
Feeling powerless?
Anxious? Depressed? Panicking?
Show up. Work. https://mastodon.social/@grimalkina/115481201032837751

bag_of_words: Bag of words (2008)
Five text collections in the form of bags-of-words, i.e. a bipartite document–word network. Left nodes are documents and right nodes are words. Edge weights are multiplicities. .
This network has 13919 nodes and 746316 edges.
Tags: Informational, Text, Bipartite, Weighted, Metadata
https://

Parallel Needleman-Wunsch on CUDA to measure word similarity based on phonetic transcriptions
Dominic Plein
https://arxiv.org/abs/2509.01654 https://arxiv.…

Parallel Needleman-Wunsch on CUDA to measure word similarity based on phonetic transcriptions
We present a method to calculate the similarity between words based on their phonetic transcription (their pronunciation) using the Needleman-Wunsch algorithm. We implement this algorithm in Rust and parallelize it on both CPU and GPU to handle large datasets efficiently. The GPU implementation leverages CUDA and the cudarc Rust library to achieve significant performance improvements. We validate our approach by constructing a fully-connected graph where nodes represent words and edges have wei…

Warm words, thin results: White House meeting lifts Ukraine, but tough road ahead: https://benborges.xyz/2025/08/19/warm-words-thin-results-white.html

What happens after you get traded? NFL players explain, in their own words https://www.nytimes.com/athletic/6771233/2025/11/03/nfl-trade-deadline-players-explain/

wordnet: WordNet relationships
A network of English words from the WordNet. Node is a word, and edge denotes relationships between words (synonymy, hyperonymy, meronymy, etc.). The date at which this network was extracted from WordNet is not unknown.
This network has 146005 nodes and 656999 edges.
Tags: Informational, Language, Unweighted
htt…

Group Actions and Some Combinatorics on Words with $\mathbf{vtm}$
John Machacek
https://arxiv.org/abs/2509.26613 https://arxiv.org/pdf/2509.26613

Group Actions and Some Combinatorics on Words with $\mathbf{vtm}$
We introduce generalizations of powers and factor complexity via orbits of group actions. These generalizations include concepts like abelian powers and abelian complexity. It is shown that this notion of factor complexity cannot be used to recognize Sturmian words in general. Within our framework, we establish square avoidance results for the ternary squarefree Thue--Morse word $\mathbf{vtm}$. These results go beyond the usual squarefreeness of $\mathbf{vtm}$ and are proved using Walnut. Lastl…

wordnet: WordNet relationships
A network of English words from the WordNet. Node is a word, and edge denotes relationships between words (synonymy, hyperonymy, meronymy, etc.). The date at which this network was extracted from WordNet is not unknown.
This network has 146005 nodes and 656999 edges.
Tags: Informational, Language, Unweighted
htt…

reuters: Reuters news stories (1987, 2000)
A bipartite network of Reuters news stories and words. Edges connect each story to all the words it contains.
This network has 1065176 nodes and 60569726 edges.
Tags: Informational, Language, Unweighted
https://networks.skewed.de/net/reuters…

Raiders QB Geno Smith Sends Blunt Message on Colts Defense https://heavy.com/sports/nfl/las-vegas-raiders/geno-smith-colts-defense/?adt_ei=[email]

bible_nouns: Bible noun phrases
A network of noun phrases (places and names) in the King James Version of the Bible. Each node is a noun phrase, and an edge exists if the noun phrases co-occur in a Bible verse. Edge weight denotes how often the two words co-occur.
This network has 1773 nodes and 9131 edges.
Tags: Informational, Language, Weighted

With apologies to 2001:
My God, it's full of vowels...
I literally got nothing but vowels with my three starter words. #Wordle
Wordle 1 598 4/6
⬛🟨⬛⬛⬛
⬛⬛🟨🟨⬛
⬛⬛⬛⬛⬛
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wiki_article_words: Wikipedia article-words (en) (2010)
A bipartite network of English Wikipedia articles and the words they contain. The edge weight gives the number of times a word appeared in the connected article.
This network has 276739 nodes and 2941902 edges.
Tags: Informational, Language, Weighted
https://

Word Chain Generators for Prefix Normal Words
Duncan Adamson, Moritz Dudey, Pamela Fleischmann, Annika Huch
https://arxiv.org/abs/2508.19619 https://arxiv.…

Word Chain Generators for Prefix Normal Words
In 2011, Fici and Lipták introduced prefix normal words. A binary word is prefix normal if it has no factor (substring) that contains more occurrences of the letter 1 than the prefix of the same length. Among the open problems regarding this topic are the enumeration of prefix normal words and efficient testing methods. We show a range of characteristics of prefix normal words. These include properties of factors that are responsible for a word not being prefix normal. With word chains and gen…

Words Won’t Stop Chicago: Raiders Need More Than Admiration https://raiderramble.com/2025/09/27/words-wont-stop-chicago-raiders-need-more-than-admiration/

Raiders QB Geno Smith Gets Strong Words After Loss to Bears https://heavy.com/sports/nfl/las-vegas-raiders/geno-smith-words-bears-loss/?adt_ei=[email]

bag_of_words: Bag of words (2008)
Five text collections in the form of bags-of-words, i.e. a bipartite document–word network. Left nodes are documents and right nodes are words. Edge weights are multiplicities. .
This network has 10336 nodes and 353160 edges.
Tags: Informational, Text, Bipartite, Weighted, Metadata
https://

Bears' Ben Johnson gives strong words after beating Raiders https://www.sportingnews.com/us/nfl/chicago-bears/news/bears-ben-johnson-gives-strong-words-after-beating-raiders/5cddd59a03f01097946ee496

wiki_article_words: Wikipedia article-words (en) (2010)
A bipartite network of English Wikipedia articles and the words they contain. The edge weight gives the number of times a word appeared in the connected article.
This network has 276739 nodes and 2941902 edges.
Tags: Informational, Language, Weighted
https://

wordnet: WordNet relationships
A network of English words from the WordNet. Node is a word, and edge denotes relationships between words (synonymy, hyperonymy, meronymy, etc.). The date at which this network was extracted from WordNet is not unknown.
This network has 146005 nodes and 656999 edges.
Tags: Informational, Language, Unweighted
htt…

bag_of_words: Bag of words (2008)
Five text collections in the form of bags-of-words, i.e. a bipartite document–word network. Left nodes are documents and right nodes are words. Edge weights are multiplicities. .
This network has 13919 nodes and 746316 edges.
Tags: Informational, Text, Bipartite, Weighted, Metadata
https://

Derek Carr Issues Eye-Opening Words on Raiders Run Game https://heavy.com/sports/nfl/las-vegas-raiders/derek-carr-eye-opening-words/?adt_ei=[email]

wiki_article_words: Wikipedia article-words (en) (2010)
A bipartite network of English Wikipedia articles and the words they contain. The edge weight gives the number of times a word appeared in the connected article.
This network has 276739 nodes and 2941902 edges.
Tags: Informational, Language, Weighted
https://

bag_of_words: Bag of words (2008)
Five text collections in the form of bags-of-words, i.e. a bipartite document–word network. Left nodes are documents and right nodes are words. Edge weights are multiplicities. .
This network has 13919 nodes and 746316 edges.
Tags: Informational, Text, Bipartite, Weighted, Metadata
https://

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…

yahoo_ads: Yahoo! advertisement words
A network of words extracted from phrases on which advertisers bid, in Yahoo! advertisements. A node is a word and a directed edge (i, j) denotes word i comes after the word j.
This network has 653260 nodes and 2931708 edges.
Tags: Informational, Language, Unweighted
https://

yahoo_ads: Yahoo! advertisement words
A network of words extracted from phrases on which advertisers bid, in Yahoo! advertisements. A node is a word and a directed edge (i, j) denotes word i comes after the word j.
This network has 653260 nodes and 2931708 edges.
Tags: Informational, Language, Unweighted
https://

wiki_article_words: Wikipedia article-words (en) (2010)
A bipartite network of English Wikipedia articles and the words they contain. The edge weight gives the number of times a word appeared in the connected article.
This network has 276739 nodes and 2941902 edges.
Tags: Informational, Language, Weighted
https://

yahoo_ads: Yahoo! advertisement words
A network of words extracted from phrases on which advertisers bid, in Yahoo! advertisements. A node is a word and a directed edge (i, j) denotes word i comes after the word j.
This network has 653260 nodes and 2931708 edges.
Tags: Informational, Language, Unweighted
https://

reuters: Reuters news stories (1987, 2000)
A bipartite network of Reuters news stories and words. Edges connect each story to all the words it contains.
This network has 1065176 nodes and 60569726 edges.
Tags: Informational, Language, Unweighted
https://networks.skewed.de/net/reuters…

bag_of_words: Bag of words (2008)
Five text collections in the form of bags-of-words, i.e. a bipartite document–word network. Left nodes are documents and right nodes are words. Edge weights are multiplicities. .
This network has 402660 nodes and 69679427 edges.
Tags: Informational, Text, Bipartite, Weighted, Metadata
https://