通过数据集成来清理和丰富数据:建立意大利学术界的网络
Irene Finocchi1, Alessio Martino2, Fariba Ranjbar1
1Luiss Guido Carli, Department of Business and Management, Viale Romania, 32, Rome, 00197, Italy.
Scientific data
|February 21, 2025
概括
本研究介绍了意大利学术合著的图书统计网络,详细介绍了合作和研究人员数据. 这个经过验证的网络为社交网络分析和文献计量研究提供了宝贵的见解.
科学领域:
- 图书统计学 图书统计学
- 社交网络分析 社交网络分析
- 科学测量公司的科学测量.
背景情况:
- 了解学术合作对于评估研究影响和生产力至关重要.
- 现有的文献计量数据集往往缺乏全面的语义信息或广泛的覆盖范围.
研究的目的:
- 在意大利学术界构建和验证一个全面的共同作者合作的图书统计网络.
- 用各种语义数据丰富网络,用于先进的分析应用.
主要方法:
- 将意大利大学和研究部的教师数据与Semantic Scholar的出版数据集成.
- 开发一个由38,220个节点 (研究人员) 和507,050个边缘 (合作) 组成的图书统计网络.
- 验证网络的可靠性和分析其图形理论属性.
主要成果:
- 创建一个大规模的,含义丰富的图书识别网络.
- 该网络包含有关性别的数据,图书识别索引,研究领域和时间信息.
- 成功验证解决了数据集成方面的挑战,确保了网络可靠性.
结论:
- 发展起来的意大利学术共同作者网络是用于参考资料和社交网络分析的强大数据集.
- 该网络丰富的语义特征使得深入的实验研究成为可能.
- 该资源促进了学术合作动态和科学生产力的研究.
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