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Natural Sciences Meet Social Sciences: Census Data Analytics for Detecting Home Language Shifts

机译：自然科学符合社会科学：人口普查数据分析检测家庭语言班次

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As we are living in a global environment, it is not unusual to have more than one languages or dialects used in a country. Examples include Canada in the Americas, Singapore in Asia, and Switzerland in Europe. With the initiatives of globalization, many people immigrate or live in a country other than their birthplace. As a result, different people in the same country may have different home language (i.e., first language). For instance, as a nation composed of a highly diverse language population, Canada provides a unique opportunity to study the factors causing certain languages (or families of language) to be lost over subsequent generations among allophones (i.e., people whose mother tongue is neither English or French). In this paper, we focus on census data analytics. Specifically, we analyze census microdata by exploring machine learning and data mining techniques-such as decision tree induction, random forest, and categorical naive Bayes-to study the influence of various social and economic factors on the probability that allophones adopt official languages as their language spoken at home. This study is a showcase where natural sciences and engineering (NSE) meet social sciences, in which NSE solutions (e.g., census data analytics) are applicable for the study of social science related phenomena (e.g., successful detection of shifts in home languages).
机译：随着我们生活在全球环境中，拥有一个不同的语言或国家方言并不罕见。例如加拿大在美洲，新加坡在亚洲，欧洲瑞士。随着全球化的举措，许多人在其出生地以外的国家移民或生活。因此，同一个国家的不同人可能有不同的家庭语言（即，第一语言）。例如，作为一个由高度不同的语言人口组成的国家，加拿大提供了一个独特的机会，可以研究导致某些语言（或语言的家庭）在随后的一代人中丢失的因素（即，母语既不英语的人。或法语）。在本文中，我们专注于人口普查数据分析。具体而言，我们通过探索机器学习和数据挖掘技术 - 例如决策树感应，随机森林和分类的天真贝叶斯 - 研究各种社会和经济因素对诸如其语言的概率的影响，分析了人口普查在家里说。本研究是一个展示自然科学和工程（NSE）符合社会科学的展示，其中NSE解决方案（例如，人口普查数据分析）适用于社会科学相关现象的研究（例如，在家庭语言中成功地检测转变）。

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