城市语言使用的地理位置差异
Geolocation differences of language use in urban areas
摘要：
在社交媒体时代，自然语言数据的可用性激增，催生了大量应用，如情感分析和意见挖掘。与此同时，精确地理定位信息的日益可用性使环境变化和疾病传播等全球现象可视化成为可能。然而，跟踪语言使用的空间变化的机会在很大程度上被忽视了，特别是在小的空间尺度上。在这里，我们探索使用Twitter数据与精确的地理位置信息，以解决语言使用的空间变化在城市规模下降到单个城市街区。我们确定了几个类别的语言标记可能会显示出独特的使用模式，并开发定量的方法来可视化与这些模式相关的空间分布。我们的分析集中在比较来自同一类别的对比对的推文分布，每个由一组令牌定义。我们的工作表明，小规模的变化分析可以提供独特的信息，语言使用和社会背景之间的相关性，这是非常有价值的广泛领域，从语言科学和商业广告的社会服务。
英文摘要：
The explosion in the availability of natural language data in the era of social media has given rise to a host of applications such as sentiment analysis and opinion mining. Simultaneously, the growing availability of precise geolocation information is enabling visualization of global phenomena such as environmental changes and disease propagation. Opportunities for tracking spatial variations in language use, however, have largely been overlooked, especially on small spatial scales. Here we explore the use of Twitter data with precise geolocation information to resolve spatial variations in language use on an urban scale down to single city blocks. We identify several categories of language tokens likely to show distinctive patterns of use and develop quantitative methods to visualize the spatial distributions associated with these patterns. Our analysis concentrates on comparison of contrasting pairs of Tweet distributions from the same category, each defined by a set of tokens. Our work shows that analysis of small-scale variations can provide unique information on correlations between language use and social context which are highly valuable to a wide range of fields from linguistic science and commercial advertising to social services.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
