MiS Preprint Repository

We have decided to discontinue the publication of preprints on our preprint server as of 1 March 2024. The publication culture within mathematics has changed so much due to the rise of repositories such as ArXiV ( that we are encouraging all institute members to make their preprints available there. An institute's repository in its previous form is, therefore, unnecessary. The preprints published to date will remain available here, but we will not add any new preprints here.

MiS Preprint

A Novel Local Centrality Measure for Contextual Diversity in Semantic Networks

Haim Cohen, Yinon Nachshon, Paz M. Naim, Jürgen Jost, Emil Saucan and Anat Maril


This paper offers a novel local centrality-based betweenness measure designed to capture, within a semantic network, the extent to which a word is characterized by contextual diversity (CD). A CD word is one that occurs in several different and distinct contexts. After presenting the measure, we demonstrate empirically that it differs from other leading central measures, such as betweenness, degree, closeness, and the number of triangles. We then examine the relationship between the CD level of a word, as determined by the novel centrality measure, and the accessibility to knowledge stored in memory. To do so, we show that CD words are significantly more effective than non-CD words in facilitating the retrieval of subsequent words. CD words themselves, however, are not retrieved significantly faster than non-CD words. These results were obtained for a serial semantic memory task, where the word’s location constitutes a significant mediator in the relationship between the proposed measure and accessibility to knowledge stored in memory. Finally, we interpret these results as a psychological validation of our proposed measure.


Related publications

2022 Journal Open Access
Haim Cohen, Yinon Nachshon, Paz M. Naim, Jürgen Jost, Anat Maril and Emil Saucan

Local detour centrality : a novel local centrality measure for weighted networks

In: Applied network science, 7 (2022), p. 72