对Twitter (X) 上与毒品有关的歌词的流行率和趋势的分析:定量方法
Waylon Luo1, Ruoming Jin1, Deric Kenne2
1Department of Computer Science, Kent State University, Kent, OH, United States.
JMIR formative research
|January 3, 2025
概括
这项研究分析了X (以前的Twitter) 上的毒品歌词,发现大麻素,阿片类药物,兴奋剂和幻觉剂是最常见的. 先进的模型预测,社交媒体上毒品歌词引用的数量略有下降.
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
- 公共卫生 公共卫生
背景情况:
- 毒品文化在流行音乐和社交媒体中普遍存在.
- 以前的研究已经分别检查了社交媒体和音乐中的药物滥用内容.
- 社交媒体和音乐歌词中药物滥用内容的交集仍然未被充分探索.
研究的目的:
- 调查流行音乐歌词中的毒品趋势,这些歌词在X (以前的Twitter) 上分享.
- 识别和分类歌词中提到的流行药物,并分析艺术家/类型特征.
- 开发未来药物趋势的预测模型,并了解与药物歌词相关的用户行为.
主要方法:
- 通过X流媒体API收集了2015-2017年的X数据.
- 利用Genius API进行药物歌词和史密斯-沃特曼算法进行文本匹配.
- 使用时间序列模型 (线性回归,Facebook Prophet,NIXTLA TimeGPT-1) 来进行趋势预测.
主要成果:
- 分析了超过197亿条帖子,确定了150,746条引用毒品歌词的帖子.
- 大麻素,阿片类药物,兴奋剂和幻觉剂是被引用最多的药物类别.
- 拉普和哈类型占主导地位,男性艺术家是主要的表演者.
结论:
- 识别了X上的毒品歌词,作为预测与毒品有关的事件的新,关键数据子集.
- 证明了先进的时间序列预测工具用于分析社交媒体趋势的有效性.
- 提供了关于社交媒体对公众对药物使用的看法和行为的影响的见解.
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