How does language differ across one's Facebook status updates vs. one's text messages (SMS)? In this study, we show how Facebook and SMS use differs in psycho-linguistic characteristics and how these differences drive downstream analyses with an illustration of depression diagnosis. We use a sample of consenting participants who shared Facebook status updates, SMS data, and answered a standard psychological depression screener. We quantify domain differences using psychologically driven lexical methods and find that language on Facebook involves more personal concerns, experiences, and content features while the language in SMS contains more informal and style features. Next, we estimate depression from both text domains, using a depression model trained on Facebook data, and find a drop in accuracy when predicting self-reported depression assessments from the SMS-based depression estimates. Finally, we evaluate a simple domain adaption correction based on words driving the cross-platform differences and applied it to the SMS-derived depression estimates, resulting in significant improvement in prediction. Our work shows the Facebook vs. SMS difference in language use and suggests the necessity of cross-domain adaption for text-based predictions.

通过对Facebook和短消息(SMS)的语言差异进行心理语言学特征研究，本研究通过对抑郁症诊断的说明展示了这些差异如何推动下游分析。我们使用了一个共同允许分享Facebook状态更新、短消息数据外加填写标准心理抑郁症检测表的样本。我们使用基于心理学的词汇方法量化域之间的差异，并发现Facebook上的语言涉及更多的个人关注、经历和内容特征，而短信中的语言则包含更多非正式和风格特征。最后，我们评估了一个简单的领域适应纠正算法，应用于基于短信的抑郁症估计，使预测指标有了显著的提高，强调了跨领域适应对于基于文本的预测的必要性。

Facebook和短信中的跨平台语言使用差异: 以抑郁症诊断为例