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@netzschleuder@social.skewed.de
2025-08-14 13:00:08

dbpedia_occupation: Person-Occupation Affiliations (DBpedia, 2016)
A bipartite network of the affiliations between notable people and occupations, as extracted from Wikipedia by the DBpedia project.
This network has 229307 nodes and 250945 edges.
Tags: Social, Affiliation, Unweighted
networks.s…

dbpedia_occupation: Person-Occupation Affiliations (DBpedia, 2016). 229307 nodes, 250945 edges. https://networks.skewed.de/net/dbpedia_occupation

dbpedia_occupation — Person-Occupation Affiliations (DBpedia, 2016)
A bipartite network of the affiliations between notable people and occupations, as extracted from Wikipedia by the DBpedia project.

@Techmeme@techhub.social
2025-08-13 15:46:21

Chinese chip equipment supplier E-Town sues Applied Materials in the Beijing IP Court over alleged trade secret theft; Applied Materials hired two E-Town staff (Bloomberg)
bloomberg.com/news/articles/20

@raiders@darktundra.xyz
2025-08-14 23:33:26

Raiders' Ashton Jeanty shows big-play ability in joint practice with the 49ers foxsports.com/articles/nfl/rai

Raiders' Ashton Jeanty shows big-play ability in joint practice with the 49ers
The San Francisco 49ers managed to contain Las Vegas Raiders running back Ashton Jeanty during a joint practice Thursday

@arXiv_csIR_bot@mastoxiv.page
2025-10-14 11:19:59

Dynamic Network-Based Two-Stage Time Series Forecasting for Affiliate Marketing
Zhe Wang, Yaming Yang, Ziyu Guan, Bin Tong, Rui Wang, Wei Zhao, Hongbo Deng
arxiv.org/abs/2510.11323

Dynamic Network-Based Two-Stage Time Series Forecasting for Affiliate Marketing
In recent years, affiliate marketing has emerged as a revenue-sharing strategy where merchants collaborate with promoters to promote their products. It not only increases product exposure but also allows promoters to earn a commission. This paper addresses the pivotal yet under-explored challenge in affiliate marketing: accurately assessing and predicting the contributions of promoters in product promotion. We design a novel metric for evaluating the indirect contributions of the promoter, call…

@netzschleuder@social.skewed.de
2025-10-13 08:00:15

dbpedia_team: DBpedia athlete-team affiliations
Bipartite network of the affiliations (employment relations) between professional athletes and their teams, as extracted from Wikipedia by the DBpedia project.
This network has 935627 nodes and 1366466 edges.
Tags: Economic, Employment, Unweighted
netwo…

dbpedia_team: DBpedia athlete-team affiliations. 935627 nodes, 1366466 edges. https://networks.skewed.de/net/dbpedia_team

dbpedia_team — DBpedia athlete-team affiliations
Bipartite network of the affiliations (employment relations) between professional athletes and their teams, as extracted from Wikipedia by the DBpedia project.

@cowboys@darktundra.xyz
2025-08-12 22:19:21

Practice Points: George Pickens highlights contested catch ability dallascowboys.com/news/practic

Practice Points: George Pickens highlights contested catch ability
George Pickens' contested catch down the sidelines from Dak Prescott was the highlight of Tuesday's practice in Oxnard. 

@netzschleuder@social.skewed.de
2025-08-14 18:00:09

dbpedia_recordlabel: DBpedia artist-label affiliations
Bipartite networks of the affiliations (contractual relations) between artists and the record labels under which they have performed, as extracted from Wikipedia by the DBpedia project.
This network has 186758 nodes and 233286 edges.
Tags: Economic, Employment, Unweighted

dbpedia_recordlabel: DBpedia artist-label affiliations. 186758 nodes, 233286 edges. https://networks.skewed.de/net/dbpedia_recordlabel

dbpedia_recordlabel — DBpedia artist-label affiliations
Bipartite networks of the affiliations (contractual relations) between artists and the record labels under which they have performed, as extracted from Wikipedia by the DBpedia project.

@netzschleuder@social.skewed.de
2025-08-13 20:00:18

dbpedia_team: DBpedia athlete-team affiliations
Bipartite network of the affiliations (employment relations) between professional athletes and their teams, as extracted from Wikipedia by the DBpedia project.
This network has 935627 nodes and 1366466 edges.
Tags: Economic, Employment, Unweighted
netwo…

dbpedia_team: DBpedia athlete-team affiliations. 935627 nodes, 1366466 edges. https://networks.skewed.de/net/dbpedia_team

dbpedia_team — DBpedia athlete-team affiliations
Bipartite network of the affiliations (employment relations) between professional athletes and their teams, as extracted from Wikipedia by the DBpedia project.

@cowboys@darktundra.xyz
2025-08-12 22:18:32

Practice Points: George Pickens highlights contested catch ability dallascowboys.com/news/practic

Practice Points: George Pickens highlights contested catch ability
George Pickens' contested catch down the sidelines from Dak Prescott was the highlight of Tuesday's practice in Oxnard. 

@netzschleuder@social.skewed.de
2025-10-12 17:01:05

discogs_genre: Discogs artist affiliations
Two bipartite networks of the affiliations between musical artists and either musical genres or musical "styles," as given in the discogs.com database. An edge indicates that a given artist was involved in a production of a particular genre or style. The date of this snapshot is uncertain.
This network has 1754838 nodes and 19033891 edges.
Tags: Informational, Relatedness, Unweighted

discogs_genre: Discogs artist affiliations. 1754838 nodes, 19033891 edges. https://networks.skewed.de/net/discogs_genre

discogs_genre — Discogs artist affiliations
Two bipartite networks of the affiliations between musical artists and either musical genres or musical "styles," as given in the discogs.com database. An edge indicates that a given artist was involved in a production of a particular genre or style. The date of this snapshot is uncertain.