Language about the future on social media as a novel marker of anxiety and depression: A big-data and experimental analysis

Cole Robertson , James Carney , Shane Trudell
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Abstract

Anxiety and depression negatively impact many. Studies suggest depression is associated with future time horizons, or how “far” into the future people tend to think, and anxiety is associated with temporal discounting, or how much people devalue future rewards. Separate studies from linguistics and economics have shown that how people refer to future time predicts temporal discounting. Yet no one—that we know of—has investigated whether future time reference habits are a marker of anxiety and/or depression. We introduce the FTR classifier, a novel classification system researchers can use to analyse linguistic temporal reference. In Study 1, we used the FTR classifier to analyse data from the social-media website Reddit. Users who had previously posted popular contributions to forums about anxiety and depression referenced the future and past more often than controls, had more proximal future and past time horizons, and significantly differed in their linguistic future time reference patterns: They used fewer future tense constructions (e.g. will), fewer high-certainty constructions (certainly), more low-certainty constructions (could), more bouletic modal constructions (hope), and more deontic modal constructions (must). This motivated Study 2, a survey-based mediation analysis. Self-reported anxious participants represented future events as more temporally distal and therefore temporally discounted to a greater degree. The same was not true of depression. We conclude that methods which combine big-data with experimental paradigms can help identify novel markers of mental illness, which can aid in the development of new therapies and diagnostic criteria.

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社交媒体上关于未来的语言是焦虑和抑郁的新标志:一项大数据和实验分析
焦虑和抑郁对许多人产生负面影响。研究表明,抑郁与未来的时间范围有关,或者人们倾向于思考未来的“多远”,焦虑与时间折扣有关,或者他们对未来奖励的贬值程度有关。语言学和经济学的单独研究表明,人们对未来时间的称呼可以预测时间折扣。然而,据我们所知,没有人调查过未来的时间参考习惯是否是焦虑和/或抑郁的标志。我们介绍了FTR分类器,这是一种新的分类系统,研究人员可以用来分析语言时间参考。在研究1中,我们使用FTR分类器来分析社交媒体网站Reddit的数据。之前在论坛上发布过关于焦虑和抑郁的热门文章的用户比对照组更频繁地提及未来和过去,他们的未来和过去时间范围更近,并且他们的语言未来时间参考模式也有显著差异:他们使用的未来时式结构更少(例如will),使用的高确定性结构更少(当然),更多的低确定性结构(可以),更多的粗模态结构(希望),以及更多的道义模态结构(必须)。这激发了研究2,一项基于调查的调解分析。自我报告的焦虑参与者表示,未来的事件在时间上更遥远,因此在时间上被更大程度地低估。抑郁症的情况并非如此。我们的结论是,将大数据与实验范式相结合的方法可以帮助识别新的精神疾病标志物,这有助于开发新的治疗方法和诊断标准。
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Current research in behavioral sciences
Current research in behavioral sciences Behavioral Neuroscience
CiteScore
7.90
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审稿时长
40 days
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