随着时间的推移,社交媒体平台上的语言简化模式
N Di Marco1, Edoardo Loru2, Anita Bonetti3
1Department of Computer Science, Sapienza University of Rome, Roma 00161, Italy.
概括
数字平台影响用户评论,导致34年来文本长度和词汇丰富度减少. 然而,用户始终引入新词,表明了超越平台效应的内在语言演变.
科学领域:
- 计算语言学 计算语言学
- 数字通信研究 数字通信研究
- 社会语言学 社会语言学
背景情况:
- 数字平台显著影响用户行为,影响两极分化,错误信息和新闻消费模式.
- 跨平台和时间的比较分析对于理解这些复杂的动态至关重要.
研究的目的:
- 调查34年来用户评论的语言特征和时间变化.
- 分析大约3亿个英语评论中的词汇量和语言丰富性,跨越各种平台和主题.
主要方法:
- 分析了来自八个不同的平台和主题的大型数据集,大约有3亿条英语评论.
- 在34年的时间里,对语言复杂性,词汇量和词汇丰富性的研究.
主要成果:
- 在各个平台和主题中观察到减少文本长度,减少词汇丰富度和减少重复性的一致模式.
- 用户在评论中引入新词的速度几乎不变,无论平台或主题如何.
- 平台对评论复杂性的影响是局部的,更广泛的社会触发因素推动了语言变化.
结论:
- 用户评论复杂性反映了内在的语言倾向和社会触发因素,而不仅仅是平台设计.
- 观察到的语言变化与语言杂交和污染的历史过程保持一致.
- 了解这些用户驱动的语言转变是理解在线通信动态的关键.
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