Abstract
This paper applies social network analysis in two experiments. In the first experiment, social network analysis is conducted on student friendship networks to find relational patterns. Then, three community detection methods are used to divide the student network. The RSiena package is used to illustrate the coevolution of friendship networks with smoking and drinking behavior. In this experiment, it was determined that in the closed network, same-sex reciprocated relationships are preferred. The second experiment analyzes a weighted
trust network that involves users trading with Bitcoin on the BTC-Alpha platform. Since the dealers of Bitcoin are anonymous, there is an urgent need to record every dealer’s credit history to prevent fraud and other security problems. The second experiment aims to improve security problems within the Bitcoin trust network by applying social network analysis.
trust network that involves users trading with Bitcoin on the BTC-Alpha platform. Since the dealers of Bitcoin are anonymous, there is an urgent need to record every dealer’s credit history to prevent fraud and other security problems. The second experiment aims to improve security problems within the Bitcoin trust network by applying social network analysis.
| Original language | English |
|---|---|
| Article number | 100065 |
| Number of pages | 12 |
| Journal | Decision Analytics Journal |
| Volume | 3 |
| Early online date | 11 May 2022 |
| DOIs | |
| Publication status | Published - Jun 2022 |
Bibliographical note
Funding: This work is partly supported by VC Research (VCR 0000176).© 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords
- social network analysis
- dynamic networks
- cryptocurrency
- RSiena