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Sharing feelings online: studying emotional well-being via automated text analysis of Facebook posts

机译:在线分享感受:通过对Facebook帖子进行自动文本分析来研究情感幸福感

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摘要

Digital traces of activity on social network sites represent a vast source of ecological data with potential connections with individual behavioral and psychological characteristics. The present study investigates the relationship between user-generated textual content shared on Facebook and emotional well-being. Self-report measures of depression, anxiety, and stress were collected from 201 adult Facebook users from North Italy. Emotion-related textual indicators, including emoticon use, were extracted form users’ Facebook posts via automated text analysis. Correlation analyses revealed that individuals with higher levels of depression, anxiety expressed negative emotions on Facebook more frequently. In addition, use of emoticons expressing positive emotions correlated negatively with stress level. When comparing age groups, younger users reported higher frequency of both emotion-related words and emoticon use in their posts. Also, the relationship between online emotional expression and self-report emotional well-being was generally stronger in the younger group. Overall, findings support the feasibility and validity of studying individual emotional well-being by means of examination of Facebook profiles. Implications for online screening purposes and future research directions are discussed.
机译:社交网站上的数字活动痕迹代表着生态数据的巨大来源,它们与个人行为和心理特征具有潜在的联系。本研究调查了在Facebook上共享的用户生成的文本内容与情感幸福之间的关系。从意大利北部的201名成年Facebook用户中收集了抑郁,焦虑和压力的自我报告指标。通过自动文本分析从用户的Facebook帖子中提取包括表情符号使用在内的与情感相关的文本指标。相关性分析显示,抑郁症,焦虑症患者在Facebook上表达负面情绪的频率更高。此外,使用表情符号表达积极情绪与压力水平负相关。在比较年龄段时,年轻用户在其帖子中报告了与情感相关的单词和表情符号使用的频率更高。此外,在年轻群体中,在线情绪表达与自我报告情绪幸福感之间的关系通常更强。总体而言,研究结果支持通过检查Facebook个人资料来研究个人情绪健康的可行性和有效性。讨论了对在线筛选的意义和未来的研究方向。

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