语言和民族语境下推特表情符号使用的实证研究

Q1 Social Sciences Online Social Networks and Media Pub Date : 2021-07-01 DOI:10.1016/j.osnem.2021.100149
Mayank Kejriwal, Qile Wang , Hongyu Li , Lu Wang
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引用次数: 28

摘要

表情符号或“图片字符”在现代数字交流中无处不在,包括社交媒体分享和智能手机短信。尽管它们无处不在,但关于它们的用法仍然存在许多问题,特别是在语言和国家的全球差异方面。这些问题很重要,部分是因为它们揭示了人们如何在社交平台上进行数字交流,但也因为它们提供了一个可以研究不同地区和文化的镜头。在本文中,我们进行了一项原则性的定量研究,从语言和国家相关性的角度来理解表情符号的使用。我们的研究涉及30种语言和30个国家,并在整整一个月的时间里收集了数千万条推文。利用统计方法和信息论,我们的研究结果表明,表情符号的使用不仅在语言和国家层面上都有很强的依赖性,而且一些语言和国家在表情符号使用的多样性方面受到更大的限制。然而,我们也发现,表情符号的“流行”,无论是在全球范围内还是在特定语言的背景下,都遵循着一种强劲而不变的趋势,这种趋势出现得相当快(仅在一天的数据中),无法用幂律或希普定律之类的分布来解释。
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An empirical study of emoji usage on Twitter in linguistic and national contexts

Emojis or ‘picture characters’ have become ubiquitous in modern-day digital communication, including social media sharing and smartphone texting. Despite this ubiquity, many questions remain about their usage, especially with respect to global variations in language and country. These questions are important, in part because they reveal how people communicate digitally on social platforms, but also because they provide a lens through which different regions and cultures can be studied. In this paper, we conduct a principled, quantitative study to understand emoji usage in terms of linguistic and country correlates. Our study involves 30 languages and countries each, and is conducted over tens of millions of tweets collected from the Twitter decahose over an entire month. Drawing on both statistical measures and information theory, our results reveal that, not only does emoji usage have strong dependencies at both the language and country level, but that some languages and countries are much more constrained in the diversity of their emoji usage. However, we also discover that the ‘popularity’ of emojis, both globally and within the context of a given language, follows a robust and invariant trend that emerges fairly quickly (over just a day’s worth of data) and cannot be explained either by a power-law or Heap’s law-like distribution.

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来源期刊
Online Social Networks and Media
Online Social Networks and Media Social Sciences-Communication
CiteScore
10.60
自引率
0.00%
发文量
32
审稿时长
44 days
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