PLOS ONE2013-12-11 1:12 AM

Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach 通过社交语言分析人的性格,性别和年龄:开放词汇方法

Abstract We analyzed 700 million words, phrases, and topic instances collected from the Facebook messages of 75,000 volunteers, who also took standard personality tests, and found striking variations in language with personality, gender, and age. In our open-vocabulary technique, the data itself drives a comprehensive exploration of language that distinguishes people, finding connections that are not captured with traditional closed-vocabulary word-category analyses. Our analyses shed new light on psychosocial processes yielding results that are face valid (e.g., subjects living in high elevations talk about the mountains), tie in with other research (e.g., neurotic people disproportionately use the phrase ‘sick of’ and the word ‘depressed’), suggest new hypotheses (e.g., an active life implies emotional stability), and give detailed insights (males use the possessive ‘my’ when mentioning their ‘wife’ or ‘girlfriend’ more often than females use ‘my’ with ‘husband’ or 'boyfriend’). To date, this represents the largest study, by an order of magnitude, of language and personality. 论文摘要 我们分析了7亿个单词,短语以及从75000个志愿者的Facebook消息中收集的话题实例。 我们也进行了标准的性格测试,发现性格,性别和年龄的差异导致非常惊人的语言变化。 用我们的开放词汇技术, 这些数据本身推动了对语言全面探索,探索如何通过语言区分人群。 这一联系的发现是我们在传统的封闭词汇字类分析中无法得到的。 我们的研究在某些方面揭示了新曙光,包括社会心理过程产生的有价值的结果(例如,生活在高海拔的人群讨论高山), 配合其他研究(例如, 神经质的人不同程度地使用短语“讨厌”或者“郁闷”), 提出新的假设(例如,积极的生活暗示情绪稳定), 并且提出详细的见解(男性在提到他们的妻子或者女朋友的时候使用所有格的“my"比女性在提到它们地丈夫或者男朋友地时候使用所有格“my” 要多很多 )。 到今天为止,这代表了最大规模的对语言和性格的研究。

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