脱人化和令人厌恶的语言对移民态度的影响:对推特数据的情感分析
Katherine S Wahrer1, Cynthia J Najdowski2, John V Passarelli3
1School of Criminal Justice, University at Albany, State University at New York, Albany, NY, USA.
概括
社交媒体内容将非人道化和对移民的厌恶联系起来,令人惊的是,随着时间的推移,对移民的积极态度有所增加. 这表明在线平台对公众对移民的看法产生了复杂的,意想不到的影响.
科学领域:
- 社会心理学 社会心理学
- 计算社会科学 计算社会科学
- 媒体研究 媒体研究
背景情况:
- 对移民的负面态度往往与非人性化和厌恶有关.
- 尽管社交媒体广泛使用,但社交媒体对这些态度的影响仍未得到充分研究.
- 了解在线话语的动态对于论研究至关重要.
研究的目的:
- 调查社交媒体上接触非人性化和令人厌恶的语言如何随着时间的推移影响人们对移民的态度.
- 用机器学习和情绪分析分析Twitter数据来探索这些关系.
- 确定特定语言类型对公众情绪的因果关系.
主要方法:
- 利用推特数据分析与移民有关的推特.
- 采用机器学习和情绪分析技术.
- 检查了在线话语中非人性化和令人厌恶的语言的普遍性.
主要成果:
- 不人道和/或引起厌恶的语言存在于66%的样本移民相关推文中.
- 接触这种语言与随着时间的推移增加对移民的积极情绪有着意想不到的联系.
- 格兰杰因果关系观察到非人性化的语言,取决于对政治关系的控制.
结论:
- 社交媒体的曝光可以以意想不到的方式塑造公众对移民的态度.
- 在线语言,情绪和移民情绪之间的关系是复杂的.
- 需要进一步的研究才能充分理解社交媒体对社会态度的长期影响.
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