Subjects: Psychology >> Applied Psychology submitted time 2022-03-06
Abstract：
[Objective] This study aims to explore the relationship between staying up late, different development levels of cities and life satisfaction with the method of big data in Weibo, so as to increase the understanding of life satisfaction of contemporary people. [Method]The users in Weibo were divided into those who stayed up late and didn't stay up late in first-tier cities and other cities according to user’s information of blog posting. In addition, the statistical difference in life satisfaction between people who stayed up late and didn't stay up late in different areas was compared. [Results] (1) The life satisfaction of Weibo users who stayed up late was significantly higher than that of non-staying up late group (t = 11.768, p < 0.05); (2) Life satisfaction of Weibo users in first-tier cities was significantly lower than that of users in other cities (t =-4.135, p < 0.05); (3) The life satisfaction of staying up late in first-tier cities was significantly lower than that of staying up late in other cities (p < 0.05), and there was no statistically significant difference between non-staying up late in first-tier cities and non-staying up late in other cities (p > 0.05); (4) The life satisfaction of staying up late in first-tier cities was significantly higher than that of non-staying up late in first-tier cities (p < 0.05), and that of staying up late in other cities was significantly higher than that of non-staying up late (p < 0.05). [Conclusion] The staying up late behavior of contemporary Weibo users will improve their life satisfaction to a certain extent. However, the life satisfaction of Weibo users in first-tier cities is lower than that of Weibo users in other cities. "
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Applied Psychology submitted time 2020-02-05
Abstract： [Objective] To explore the influence of public health emergencies on the psychological state of the public, and understand its changing characteristics and rules. [Methods] We acquire active Weibo users from 2020/1/13 to 2020/2/26 at first, and extract features from these users’ data, including word frequency, negative (anxiety, depression and force), positive (life satisfaction and oxford happiness) and social attitudes (social risk judgment and anger) index. We then compare the differences of psychological characteristics between 2020/1/13-2020/1/19 and 2020/1/20-2020/1/26. [Results] The result indicates that the frequency of negative emotional words (t=-18.533, p < 0.05) and anxious words were increased (t=-17.433, p < 0.05), family words (t=7.907, p < 0.05) and friend words decreased (t=6.897, p < 0.05) after 20-th. Meanwhile, anxiety (t=-35.962, p < 0.05), depression (t=-10.717, p < 0.05) and obsessiveness (t=-24.755, p < 0.05) were increased. Oxford happiness (t=3.120, p < 0.05) and life satisfaction (t=5.500, p < 0.05) were decreased. The levels of social risk judgment (t=-8.832, p < 0.05) and anger (t=-11.415, p < 0.05) were increased. [Limitations] The weekly measurement of the data is considered as a relatively large scale, which has a certain influence on reflecting the trend of social mentality timely. [Conclusions] After the official confirmation and attention to the incident, the overall state of mind of the society showed an increase in negative emotions such as anxiety and anger, as well as a decrease in well-being and an increase in sensitivity to social risks.
Peer Review Status:Awaiting Review
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