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 Subjects: Computer Science >> Computer Application Technology submitted time 2020-03-08
Abstract： Personality affects the individual's work and life style, and has important guiding significance for the individual's psychological counseling and career development. Traditional methods use personality scales to evaluate personality scores, which include problems such as individual refusal to answer and blind answering. In recent years, with the development of machine learning, new ideas have been provided for personality recognition. This article uses participants' self-introduction videos and Big Five personality scale scores to obtain different prediction models for different personality dimensions through key point extraction, feature dimension reduction, modeling, and iterative tuning. This article uses participants' self-introduction videos and Big Five personality scale scores to obtain different prediction models for different personality dimensions through key point extraction, feature dimension reduction, modeling, and iterative tuning. The test results show that the personality prediction model based on the self-introduction video is close to or achieves medium correlation in all dimensions, and can provide non-intrusive automatic personality recognition,, which provides new ideas for personality measurement.
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
Subjects: Psychology >> Applied Psychology submitted time 2019-01-21
Abstract： 人们在思考或行动上所偏好的时间方向在一定程度上影响行为，而行为会影响生活状态，据此我们希望探讨时间取向与人的主观幸福感是否有关。本研究利用微博大数据，收集了2010至2017年共64160名活跃用户的微博，通过关键词提取以及数据分析发现，主观幸福感与未来词频之间存在中等强度的相关（r = 0.404, p < 0.01），与现在词频及过去词频之间呈弱相关；将用户按时间取向词频分组后，高词频组的主观幸福感显著高于低词频组（t = 67.442 , p < 0.001），同时我们也发现了主观幸福感与时间取向词频均有逐年下降的趋势。研究结果说明未来时间取向可作为主观幸福感的预测指标，本研究为利用微博大数据预测心理健康提供了新的方向。
Peer Review Status:Awaiting Review
Subjects: Psychology >> Social Psychology Subjects: Computer Science >> Computer Application Technology submitted time 2018-05-21
Abstract：
[Background] The adverse effects of childhood sexual abuse experience on female physical and psychological health are enduring. However, few studies have focused on the psychological characteristics of this group when they grew up.
[Objective] The purpose of this study was to explore the difference in psychological characteristics including social attitudes, well-being, and mental health between the females with sexual abuse experience in childhood (CSA group) and females without this experience (control group) based on the microblogging data calculation model.
[Methods] This study collected 46 victims (all females) and 46 non-victims (sex matching with CSA group) on Sina Weibo, crawled all the microblogs of the selected users and and calculate its score on various psychological characteristics by microblogging data calculation model.
[Results] Using independent sample t-test, the results showed that there were significant differences in social attitudes, well-being, and especially mental health. At the same time, we also found that there were differences in microblog behavior characteristics between the two groups. Compared with non-victims, the victims had higher scores in depression, stress and other health characteristics, and lower scores in psychological characteristics such as life satisfaction and self-acceptance. However, they did not reach the critical thresholds for the diagnosis of mental diseases.
[Limitations] The psychological features obtained from microblogging data calculation model can not completed equivalent to the psychological features obtained from psychological scales and can not replace the rigid psychological measurement.
[Conclusion] The childhood sexual abuse experience has negative effect on female. However, this effect is not sufficient to meet the threshold criteria for mental illness.
Peer Review Status:Awaiting Review
Hits
Hits
Downloads
Comment