"我今晚在蓝天":从一年的社会数据中获得的洞察力
Andrea Failla1,2, Giulio Rossetti2
1Department of Computer Science, University of Pisa, Pisa, Italy.
PloS one
|November 5, 2024
概括
一个新的Bluesky Social数据集提供了来自400万用户的2.35亿多条帖子,解决了用于计算社会科学研究的社交媒体数据短缺问题. 该资源使得在线行为和内容传播的新分析成为可能.
科学领域:
- 计算社会科学 计算社会科学
- 数字社会学 数字社会学
- 数据科学数据科学数据科学
背景情况:
- 在线社交空间面临着越来越多的虚假信息. 对社交媒体API的有限访问限制了研究数据的可用性. 计算社会科学受到这种数据稀缺的阻碍.
研究的目的:
- 解决公开可用的社交媒体数据的短缺问题. 为分析在线社交互动和用户生成内容提供全面的数据集. 促进计算社会科学和数字行为方面的研究.
主要方法:
- 从Bluesky Social收集了一个大规模的数据集,包括超过400万用户的完整帖子历史记录 (81%的注册帐户).
- 包括2.35亿条帖子,以及社交互动数据 (关注,评论,转发,引用).
- 关于用户与料生成器 (内容推算法) 的交互和其输出的发布数据.
主要成果:
- 现在可以从Bluesky Social获得一个全面的社交互动和用户生成内容数据集.
- 该数据集包括来自400多万用户的2.35亿条帖子和详细的社交网络信息.
- 此外,还提供了关于内容推算法和用户参与这些算法的数据.
结论:
- 这一数据集为研究在线行为,内容病毒性和人机交互提供了关键的基础真相数据. 它允许对内容曝光,自我选择效应和信息传播模式进行新型分析. 这些数据的可用性对于推进计算社会科学研究至关重要.
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