用户提交的文章的完整数据集,其中包括来自Reddit的意识形态和极端偏见
Kamalakkannan Ravi1, Adan Ernesto Vela1
1University of Central Florida, Orlando, USA.
Data in brief
|September 17, 2024
概括
这项研究分析了来自Reddit的152万篇文章,以了解在线社区的意识形态和极端偏见. 调查结果揭示了激进化和主流政治讨论中的语言模式.
科学领域:
- 计算社会科学 计算社会科学
- 自然语言处理自然语言处理.
- 媒体研究 媒体研究
背景情况:
- 在线社区,特别是Reddit,主办了各种各样的意识形态讨论.
- 了解共享内容中的偏见对于媒体素养至关重要.
- 以前的研究往往侧重于二元政治分歧,忽视了极端主义内容.
研究的目的:
- 收集和分析各种Reddit社区共享的文章的大规模数据集.
- 识别和量化文本内容中的意识形态和极端偏见.
- 调查与激进化和有针对性的暴力有关的语言模式.
主要方法:
- 利用Reddit的Pushshift API从55个子网址收集了超过150万篇文章的URL.
- 分类的子网格分为"自由派"",保守派"",限制性" (极端主义) 和"未指明".
- 标注了相关性和偏见验证的文章的一个子集.
主要成果:
- 为偏见分析编制了152万篇文章的综合数据集.
- 能够检查主流意识形态和极端主义在线社区的语言使用情况.
- 提供了激进化子公司的话语分析的基础.
结论:
- 这项研究提供了一个庞大而多样化的数据集,用于研究在线意识形态偏见.
- 对语言模式的洞察力可以帮助识别和减轻极端偏见.
- 这些发现有助于了解在线潜在有害内容的传播.
相关概念视频
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