@inproceedings{853aa1b30aab453394ecc500e474d144,
title = "Can One Hear the Position of Nodes?",
abstract = "Wave propagation through nodes and links of a network forms the basis of spectral graph theory. Nevertheless, the sound emitted by nodes within the resonating chamber formed by a network are not well studied. The sound emitted by vibrations of individual nodes reflects the structure of the overall network topology but also the location of the node within the network. In this article a sound recognition neural network is trained to infer centrality measures from the nodes{\textquoteright} wave-forms. In addition to advancing network representation learning, sounds emitted by nodes are plausible in most cases. Auralization of the network topology may open new directions in arts, competing with network visualization.",
keywords = "Auralization, Centrality, Deep learning, Diffusion",
author = "Rami Puzis",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 11th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2022 ; Conference date: 08-11-2022 Through 10-11-2022",
year = "2023",
month = jan,
day = "1",
doi = "10.1007/978-3-031-21131-7_50",
language = "English",
isbn = "9783031211300",
series = "Studies in Computational Intelligence",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "649--660",
editor = "Hocine Cherifi and Mantegna, {Rosario Nunzio} and Rocha, {Luis M.} and Chantal Cherifi and Salvatore Micciche",
booktitle = "Complex Networks and Their Applications XI - Proceedings of The 11th International Conference on Complex Networks and Their Applications",
address = "Germany",
}