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@netzschleuder@social.skewed.de
2025-12-02 20:00:05

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

bag_of_words: Bag of words (2008). 13919 nodes, 746316 edges. https://networks.skewed.de/net/bag_of_words#nips

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. After tokenization and removal of stopwords, the vocabulary of unique words was truncated by only keeping words that occurred more than ten times. Individual document names (i.e. a identifier for each docID) are not provided for copyright reasons.

@karlauerbach@sfba.social
2026-01-03 23:29:00

My prediction:
The return half of many round trip tickets held by US citizens to locations outside of the US will not be used.
Why will they not be used?
Because the return trip home will be in a body bag.
In other words, I am predicting that given the US actions (not merely today's invasion de jour), that US overseas travelers will become popular and easy targets for those who chose to use violence in response to US acts.

@netzschleuder@social.skewed.de
2025-11-20 23:00:05

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

bag_of_words: Bag of words (2008). 10336 nodes, 353160 edges. https://networks.skewed.de/net/bag_of_words#kos

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. After tokenization and removal of stopwords, the vocabulary of unique words was truncated by only keeping words that occurred more than ten times. Individual document names (i.e. a identifier for each docID) are not provided for copyright reasons.

@netzschleuder@social.skewed.de
2026-01-17 03:00:05

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

bag_of_words: Bag of words (2008). 13919 nodes, 746316 edges. https://networks.skewed.de/net/bag_of_words#nips

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. After tokenization and removal of stopwords, the vocabulary of unique words was truncated by only keeping words that occurred more than ten times. Individual document names (i.e. a identifier for each docID) are not provided for copyright reasons.

@netzschleuder@social.skewed.de
2026-01-15 08:00:07

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
…

bag_of_words: Bag of words (2008). 67963 nodes, 3710420 edges. https://networks.skewed.de/net/bag_of_words#enron

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. After tokenization and removal of stopwords, the vocabulary of unique words was truncated by only keeping words that occurred more than ten times. Individual document names (i.e. a identifier for each docID) are not provided for copyright reasons.

@netzschleuder@social.skewed.de
2026-01-12 03:00:05

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

bag_of_words: Bag of words (2008). 10336 nodes, 353160 edges. https://networks.skewed.de/net/bag_of_words#kos

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. After tokenization and removal of stopwords, the vocabulary of unique words was truncated by only keeping words that occurred more than ten times. Individual document names (i.e. a identifier for each docID) are not provided for copyright reasons.

@netzschleuder@social.skewed.de
2025-12-12 11:00:04

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

bag_of_words: Bag of words (2008). 10336 nodes, 353160 edges. https://networks.skewed.de/net/bag_of_words#kos

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. After tokenization and removal of stopwords, the vocabulary of unique words was truncated by only keeping words that occurred more than ten times. Individual document names (i.e. a identifier for each docID) are not provided for copyright reasons.