Relationships between Periodic Behaviors in Micro-blogging and the Users' Baseline Mood

Masashi Komori, N. Matsumura, A. Miura, Chika Nagaoka
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引用次数: 3

Abstract

Twitter messages are real-time, spontaneous reports of what the users are feeling, thinking, and doing. The frequency of posting "Tweets" oscillates periodically in one-day and seven-day cycles. These periodic patterns may be related to the individual users' baseline affective state. In order to investigate individual periodic behavior in social media, we performed a Fourier series expansion and PCA on intra-week Tweet-frequency changes of 11,570 individuals. Moreover, the relationships between the users' baseline mood and the principal component scores were investigated. High frequency in daytime tweets on weekdays was found to be linked to a low positive affective state. The larger number of posting tweets was related to the negative affective state.
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微博周期性行为与用户基线情绪的关系
Twitter消息是对用户的感受、想法和行为的实时、自发的报告。发布“tweet”的频率以一天和七天为周期周期性波动。这些周期性模式可能与个体用户的基线情感状态有关。为了研究社交媒体中的个人周期性行为,我们对11,570个人的周内推特频率变化进行了傅里叶级数展开和主成分分析。此外,研究了用户基线情绪与主成分得分之间的关系。研究发现,工作日白天发推特的频率高,与较低的积极情感状态有关。发微博次数越多,消极情感状态越强。
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