易于访问的在线社交媒体指标与错误信息共享活动有关
Júlia Számely1, Alessandro Galeazzi2, Júlia Koltai3,4
1Department of Network and Data Science, Central European University, Vienna, Austria.
Scientific reports
|November 21, 2025
概括
识别可能传播错误信息的社交媒体用户是一项挑战. 这项研究表明,推特频率和X (以前的Twitter) 账户年龄可以帮助区分分享低事实性内容的用户,有助于打击错误信息.
科学领域:
- 社会科学 社会科学 社会科学
- 计算机科学 计算机科学
- 沟通研究 沟通研究
背景情况:
- 社交媒体上的错误信息是一个重大的研究挑战.
- 识别主要分享错误信息的用户是困难的,而且需要大量的数据.
- 现有的识别虚假信息传播者的方法往往耗时.
研究的目的:
- 提出一种低障碍方法,根据社交媒体用户分享错误信息的可能性来区分社交媒体用户.
- 为了利用易于访问的社交网络指标来识别潜在的传播者低事实性内容.
- 评估推特频率和帐户年龄在预测错误信息在X (以前是Twitter) 上分享行为的有用性.
主要方法:
- 利用来自X (以前的Twitter) 的公开可用的社交网络指标.
- 分析了平均每日推特数量和帐户年龄作为虚假信息共享的预测指标.
- 研究了跟踪账户数量对这些关系的影响.
主要成果:
- 每日推特频率更高与分享事实性较低的内容有积极联系.
- 较老的账户年龄与分享低事实性内容有负面关联.
- 这些指标的影响因用户关注的帐户数量而异.
结论:
- 易于访问的社交网络指标,如推特频率和帐户年龄,可以作为一种低障碍的方法,用于初步识别潜在的虚假信息传播者.
- 这些指标可以帮助制定更有效的策略来打击社交媒体平台上的错误信息.
- 进一步的研究可以完善这些指标,以提高识别虚假信息分享者的准确性.
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