A Conceptual Framework for the Analysis of Multilayer Networks in the Humanities. Grandjean, M. In Ottawa, 2020.
A Conceptual Framework for the Analysis of Multilayer Networks in the Humanities [link]Paper  abstract   bibtex   
If network analysis has made its way into the humanities toolbox, and especially in history, it is because it helps to grasp the complexity of the objects of these disciplines. However, to understand the multidimensionality of the data requires a consequent reflection on its modeling. This paper seeks to be part of a series of publications aimed at making advanced network analysis concepts more accessible to the humanities scholars: from ontological questions to the necessary discussion of the integration of temporality in graphs, the development of typologies of uses or attempts to provide aids to interpretation. The question of multilayer networks becomes especially more and more important, whether in a general way or applied to the humanities.
@inproceedings{grandjean_conceptual_2020,
	address = {Ottawa},
	title = {A {Conceptual} {Framework} for the {Analysis} of {Multilayer} {Networks} in the {Humanities}},
	url = {https://hcommons.org/deposits/item/hc:31941/},
	abstract = {If network analysis has made its way into the humanities toolbox, and especially in history, it is because it helps to grasp the complexity of the objects of these disciplines. However, to understand the multidimensionality of the data requires a consequent reflection on its modeling. This paper seeks to be part of a series of publications aimed at making advanced network analysis concepts more accessible to the humanities scholars: from ontological questions to the necessary discussion of the integration of temporality in graphs, the development of typologies of uses or attempts to provide aids to interpretation. The question of multilayer networks becomes especially more and more important, whether in a general way or applied to the humanities.},
	language = {en-US},
	urldate = {2021-10-11},
	author = {Grandjean, Martin},
	year = {2020},
}

Downloads: 0