Semi-supervised graph labelling reveals increasing partisanship in the United States Congress

Graph labelling is a key activity of network science, with broad practical applications, and close relations to other network science tasks, such as community detection and clustering. While a large body of work exists on both unsupervised and supervised labelling algorithms, the class of random wal...

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Bibliographic Details
Published in:	Applied network science Vol. 4; no. 1; pp. 1 - 18
Main Authors:	Glonek, Max, Tuke, Jonathan, Mitchell, Lewis, Bean, Nigel
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 23.08.2019 Springer Nature B.V SpringerOpen
Subjects:	Absorption Algorithms Clustering Community detection Complexity Computer Appl. in Social and Behavioral Sciences Computer Science Glass Graph labelling Graphs Labeling Labels Markov chain Markov chains Nodes Partisanship Political networks Politics Random walk Simulation and Modeling Special Issue of the 7th International Conference on Complex Networks and Their Applications United States > US Markov chain Community detection Political networks Graph labelling Random walk
ISSN:	2364-8228, 2364-8228
Online Access:	Get full text
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