Ambient affiliation: A linguistic perspective on Twitter
Ambient affiliation: A linguistic perspective on Twitter
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环境归属：Twitter 上的语言视角
DOI：
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发表时间：
2011
影响因子：
5
通讯作者：
Michele Zappavigna
中科院分区：
文献类型：
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作者：
Michele Zappavigna
本文探讨了如何使用语言来构建微型博客服务Twitter（www.twitter.com）社区。本文运用系统功能语言学（Systemic Functional Linguistic，SFL）的语言使用理论，分析了2008年美国总统大选巴拉克奥巴马获胜后24小时内45，000条推特的结构和意义。这项分析研究了评价性语言，用于附属在推文。本文展示了一个排版惯例，标签，如何扩展其意义潜力，作为一个语言标记，引用在推文（例如#奥巴马）的评价目标。这既使语言可搜索，又用于升级调用，以与tweet中表达的价值观相关联。我们目前正在目睹电子话语的文化转变，从在线对话到这种“可搜索的谈话”。
This article explores how language is used to build community with the microblogging service, Twitter (www.twitter.com). Systemic Functional Linguistic (SFL), a theory of language use in its social context, is employed to analyse the structure and meaning of ‘tweets’ (posts to Twitter) in a corpus of 45,000 tweets collected in the 24 hours after the announcement of Barak Obama’s victory in the 2008 US presidential elections. This analysis examines the evaluative language used to affiliate in tweets. The article shows how a typographic convention, the hashtag, has extended its meaning potential to operate as a linguistic marker referencing the target of evaluation in a tweet (e.g. #Obama). This both renders the language searchable and is used to upscale the call to affiliate with values expressed in the tweet. We are currently witnessing a cultural shift in electronic discourse from online conversation to such ‘searchable talk’.