通过结构性信息和内容贡献,在基于区块链的社交网络中认可意见领袖
Chuansheng Wang1, Xuecheng Tan1, Fulei Shi1
1School of Management and Engineering, Capital University of Economics and Business, Beijing, China.
PeerJ. Computer science
|September 14, 2023
概括
在区块链社交网络中识别意见领袖对于了解信息流和内容质量至关重要. 这项研究提出了一种新的ECWM-TOPSIS方法,在确定有影响力的用户方面表现优于现有的方法.
科学领域:
- 区块链技术 区块链技术
- 社交网络分析 社交网络分析
- 信息传播 信息传播
背景情况:
- 区块链社交网络通过代币奖励和共识投票引入了新的用户责任,改变了网络动态和用户参与.
- 了解用户的影响力和识别意见领袖是管理信息传播和内容质量的关键,这些不断发展的网络.
研究的目的:
- 开发和验证一种强大的方法来识别区块链社交网络中的意见领袖.
- 整合基于结构和内容的影响指标,以进行全面的用户评估.
主要方法:
- 基于网络结构和贡献行为的定义用户影响指标.
- 开发了值权重方法,结合通过标准间相关性 (ECWM) 来处理指标相关性和多样性.
- 提出了一种通过与理想解决方案相似的订单偏好 (ECWM-TOPSIS) 的增强技术,用于识别意见领袖.
主要成果:
- 拟议的ECWM-TOPSIS方法在识别顶级N意见领袖方面表现出优异的表现,与Steemit平台上的投票分数和转发率等传统方法相比.
- 对比分析证实了ECWM-TOPSIS算法的有效性和更高的准确性.
结论:
- 在区块链社交网络中,ECWM-TOPSIS方法在识别论领袖方面取得了重大进展.
- 这种方法有助于理解信息传播动态,并促进在分散环境中发现优质内容.
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