@inproceedings{b122d6fde01940f8bb1165a286be18dc,
title = "Local Pluralistic Homophily in Networks: A New Measure Based on Overlapping Communities",
abstract = "Pluralistic homophily is an important phenomenon in social network analysis as nodes tend to associate with others that share their same communities. In this work, we present the concept of local pluralistic homophily of a node in a network, along with a method to measure it. It is based on the assortativity index proposed by other authors. We analyze the distribution of local pluralistic homophily in different networks using publicly available datasets. We identify patterns of behavior of the proposed measure that relate to various structural and topological characteristics of a network. These findings are significant because they help better understand how pluralistic homophily affects communities. Furthermore, our results suggest possible applications of local pluralistic homophily in future research.",
keywords = "Communities, Local Pluralistic Homophily, Networks",
author = "Fernando Barraza and Carlos Ramirez and Alejandro Fern{\'a}ndez",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 11th Conference on Cloud Computing, Big Data and Emerging Topics, JCC-BD and ET 2023 ; Conference date: 27-06-2023 Through 29-06-2023",
year = "2023",
doi = "10.1007/978-3-031-40942-4_6",
language = "English",
isbn = "9783031409417",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "75--87",
editor = "Marcelo Naiouf and Enzo Rucci and Franco Chichizola and {De Giusti}, Laura",
booktitle = "Cloud Computing, Big Data and Emerging Topics - 11th Conference, JCC-BD and ET 2023, Proceedings",
address = "Germany",
}