Theoretical Investigation of Harmful Information Propagation Using Physical Properties of Graphene and TeNPs: Sociophysical Approach

This study is an attempt to apply first-principles calculations in materials science, especially density functional theory (DFT) methods and physical models of telluric nanoparticles (TeNPs) and graphene, to social physics. In the recent digital society, the proliferation of harmful information has caused a wide range of problems from individual mental health to social fragmentation.

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Publication Details

Published
2024-12-17
DOI
https://doi.org/10.26717/bjstr.2024.60.009385
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.21

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article

Theoretical Investigation of Harmful Information Propagation Using Physical Properties of Graphene and TeNPs: Sociophysical Approach

Yasuko Kawahata
1 citations
Advanced Memory and Neural Computing
0.21
article

Theoretical Investigation of Harmful Information Propagation Using Physical Properties of Graphene and TeNPs: Sociophysical Approach

Yasuko Kawahata
article en
1 citations

Abstract

This study is an attempt to apply first-principles calculations in materials science, especially density functional theory (DFT) methods and physical models of telluric nanoparticles (TeNPs) and graphene, to social physics. In the recent digital society, the proliferation of harmful information has caused a wide range of problems from individual mental health to social fragmentation.

Vol. 60(1)
Rikkyo University (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 44%
Advanced Memory and Neural Computing
0.21
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Theoretical Investigation of Harmful Information Propagation Using Physical Properties of Graphene and TeNPs: Sociophysical Approach — Yasuko Kawahata · (2024) | TGRS Research Map | TGRS