分析Twitter/X上的仇恨言论动态:从对话数据的洞察力和用户交互模式的影响
António Fonseca1, Catarina Pontes1, Sérgio Moro1,2
1Instituto Universitário de Lisboa (ISCTE-IUL), ISTAR, Lisbon, Portugal.
Heliyon
|June 13, 2024
概括
这项关于Twitter/X葡萄牙网络的研究显示,关注更多账户的用户更有可能发布攻击性内容. 仇恨言论通常发生在对话的早期,通常是由外部用户引入的.
科学领域:
- 社交媒体分析 社交媒体分析
- 计算社会科学 计算社会科学
- 网络科学 网络科学
背景情况:
- 仇恨言论是像Twitter/X.X.这样的社交媒体平台上的一个重大问题.
- 了解葡萄牙语对话中仇恨言论的动态至关重要.
研究的目的:
- 分析Twitter/X葡萄牙网络中仇恨言论的特征和模式.
- 确定预测仇恨言论的发生和性质的因素.
主要方法:
- 混合方法方法结合了网络分析 (三元统计,参与转移) 和定性内容注释.
- 在Twitter/X葡萄牙社区内分析用户交互网络.
主要成果:
- 关注用户的数量可以预测用户对攻击性内容的倾向.
- 仇恨言论在对话线程的前2小时内更为普遍.
- 仇恨言论减少了互动的过渡性和个人表达.
- 外部用户是直接仇恨言论入侵的主要来源.
- 第三方间接的仇恨言论并不常见.
- 反话与非对抗性的公共话语有关.
结论:
- 用户网络的大小和早期互动动态影响仇恨言论的流行.
- 仇恨言论破坏了对话和表达的流动.
- 外部入侵是一个关键的模式,而间接干扰是罕见的.
- 反言论与典型的避免冲突的言论运作方式不同.
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