Subjects: Psychology >> Social Psychology submitted time 2023-03-27 Cooperative journals: 《心理学报》
Abstract： Heterogeneity among mental health issues has always attracted considerable attention, thereby restricting research on mental health and cognitive neuroscience. Additionally, the person-centred approach to personality research, which emphasizes population heterogeneity, has received more attention. On the other hand, the heterogeneity among depressive patients has been a problem that cannot be ignored (most studies ignored the actual situation and directly assumed sample homogeneity). A large number of empirical studies have provided evidence that isolated personality traits are often associated with depression. Only a few studies have considered the probable effect from a taxonomy perspective. Moreover, the neural mechanisms of personality types in depression remain unclear. This study aimed to reveal different personality subtypes of depressive disorders and elucidate subtypes from the perspective of resting-state functional connectivity.Personality and resting-state functional imaging data of 135 depressive patients and 133 controls were collected. First, combined with “depression diagnosis”, the personality types in depressive patients and controls were identified through functional random forest. Specifically, neuroticism and extraversion (input features) were fitted with the diagnosis of depression by a random forest model. The random seeds were set to 1234, and 500 decision trees were fitted. The performance of the model was evaluated by tenfold cross-validation. Subsequently, the random forest algorithm generated a proximity matrix that represented the similarity between paired participants. Then, based on the proximity matrix, community detection clustering analysis was conducted on depressive patients and controls, and personality types associated with depression diagnosis were obtained. Finally, we selected nodes of the subcortical network as regions of interest according to the power-264 template and calculated the functional connectivity map of the region of interest to the whole brain. Based on the functional connectivity map, the differences in resting-state functional connectivity between the main types were compared.Personality and resting-state functional imaging data of 159 depressive patients and 156 controls were collected. First, combined with “depression diagnosis”, the personality types in depressive patients and controls were identified through functional random forest. Specifically, neuroticism and extraversion (input features) were fitted with the diagnosis of depression by a random forest model. The random seeds were set to 1234, and 500 decision trees were fitted. The performance of the model was evaluated by tenfold cross-validation. Subsequently, the random forest algorithm generated a proximity matrix that represented the similarity between paired participants. Then, based on the proximity matrix, community detection clustering analysis was conducted on depressive patients and controls, and personality types associated with depression diagnosis were obtained. Finally, we selected the amygdala, hippocampus, insula (AAL atlas) and limbic network, default network, and control network (Schaefer-Yeo template) as regions of interest and calculated the functional connectivity of the subcortical regions to the networks. ANOVA was used to compare resting-state functional connectivity between the personality types.The results showed the following. (1) Depression was more common among individuals with high neuroticism and low extraversion tendencies, but there were also individuals with low neuroticism and high extraversion tendencies. The controls were more likely to be individuals with low neuroticism and high extraversion. (2) The results of resting-state functional connectivity showed no significant difference between depression and controls. (3) The functional connectivity strength of the left amygdala/insula-limbic network was significantly different across personality subtypes.In summary, the personality subtypes of depression identified by person-centred perspectives are more in line with reality and individual cognitive patterns, and they have potential clinical adaptive value. The findings of this study enhance the understanding of heterogeneity among depressive disorders.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-02-22
Abstract：摘要： 目的/意义 社交平台是谣言产生与传播的主要渠道，也是谣言传播过程中利益博弈的主要参与者。本文从博弈论的角度探究控制谣言传播的方法，为人们科学有效地治理谣言传播提供参考建议。 方法/过程 本文基于社交平台的研究视角，按照谣言发生前、传播中以及平息后三个阶段分别构建博弈模型，然后探究社交平台的策略选择及其稳定性，最后采用matlab2021b进行仿真实验验证。 结果/结论 结果表明，谣言发生前，平台策略选择主要与社会声誉价值以及政府部门的监管态度有关，提高平台对社会声誉的重视程度能够促使其加强谣言控制；传播过程中，平台的策略选择主要基于自身的商业利益出发，其次与网民的选择有关；谣言平息后，平台的策略主要取决于政府的选择，政府强化事后追责制度能够有效防止平台隐瞒事实、逃避责任行为的发生。
Peer Review Status:
Awaiting Review
Subjects: Library Science，Information Science >> Information Science submitted time 2022-12-02
Abstract：
Abstract: 【Purpose/Significance】Under the environment of social media, Internet rumors spread fast and widely, which seriously disturb the social order. Therefore, how to deal with Internet rumors has become an urgent problem to be solved in the management of Internet society. This paper explores the methods of network rumor governance from the perspective of rumor suppression strategies on social platforms, and provides reference suggestions for people to control rumor propagation scientifically and effectively.【Method/Process】Based on the rumor suppression strategy (warning and blocking) of social platforms, this paper proposes an improved SIC1-2R propagation model, and then analyzes the equilibrium point of rumors in the model and proves it. Finally, matlab2021a was used for simulation experiment.【Result/Conclusion】The results show that there are four equilibrium points of rumor propagation in the new model (no rumor equilibrium point E0, equilibrium point E1 before sealing, equilibrium point E2 before unsealing and equilibrium point E3 after unsealing), which are verified by simulation experiments. At the same time, the internal parameters of the model and the time factor have an important influence on the rumor propagation process.【Innovation/limitation】There are two innovations: (1) The rumor suppression strategy based on social platform (warning and blocking) improves the traditional SIR Communication model; (2) The stability of rumor equilibrium in the model was discussed in stages (before, before and after the number was sealed). Limitations mainly lie in the fact that the data used in the experiment are all simulated values, some parameters are set according to experience, and the governance strategy of Internet rumors is only discussed from the perspective of platform, so the research conclusions are not comprehensive enough.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Personality Psychology submitted time 2022-11-18
Abstract：
Heterogeneity among mental health issues has always attracted considerable attention, thereby restricting research on mental health and cognitive neuroscience. Additionally, the person-centred approach to personality research, which emphasizes population heterogeneity, has received more attention. On the other hand, the heterogeneity among depressive patients has been a problem that cannot be ignored (most studies ignored the actual situation and directly assumed sample homogeneity). A large number of empirical studies have provided evidence that isolated personality traits are often associated with depression. Only a few studies have considered the probable effect from a taxonomy perspective. Moreover, the neural mechanisms of personality types in depression remain unclear. This study aimed to reveal different personality subtypes of depressive disorders and elucidate subtypes from the perspective of resting-state functional connectivity. Personality and resting-state functional imaging data of 135 depressive patients and 133 controls were collected. First, combined with "depression diagnosis", the personality types in depressive patients and controls were identified through functional random forest. Specifically, neuroticism and extraversion (input features) were fitted with the diagnosis of depression by a random forest model. The random seeds were set to 1234, and 500 decision trees were fitted. The performance of the model was evaluated by tenfold cross-validation. Subsequently, the random forest algorithm generated a proximity matrix that represented the similarity between paired participants. Then, based on the proximity matrix, community detection clustering analysis was conducted on depressive patients and controls, and personality types associated with depression diagnosis were obtained. Finally, we selected nodes of the subcortical network as regions of interest according to the power-264 template and calculated the functional connectivity map of the region of interest to the whole brain. Based on the functional connectivity map, the differences in resting-state functional connectivity between the main types were compared. Personality and resting-state functional imaging data of 159 depressive patients and 156 controls were collected. First, combined with "depression diagnosis", the personality types in depressive patients and controls were identified through functional random forest. Specifically, neuroticism and extraversion (input features) were fitted with the diagnosis of depression by a random forest model. The random seeds were set to 1234, and 500 decision trees were fitted. The performance of the model was evaluated by tenfold cross-validation. Subsequently, the random forest algorithm generated a proximity matrix that represented the similarity between paired participants. Then, based on the proximity matrix, community detection clustering analysis was conducted on depressive patients and controls, and personality types associated with depression diagnosis were obtained. Finally, we selected the amygdala, hippocampus, insula (AAL atlas) and limbic network, default network, and control network (Schaefer-Yeo template) as regions of interest and calculated the functional connectivity of the subcortical regions to the networks. ANOVA was used to compare resting-state functional connectivity between the personality types. The results showed the following. (1) Depression was more common among individuals with high neuroticism and low extraversion tendencies, but there were also individuals with low neuroticism and high extraversion tendencies. The controls were more likely to be individuals with low neuroticism and high extraversion. (2) The results of resting-state functional connectivity showed no significant difference between depression and controls. (3) The functional connectivity strength of the left amygdala/insula-limbic network was significantly different across personality subtypes. In summary, the personality subtypes of depression identified by person-centred perspectives are more in line with reality and individual cognitive patterns, and they have potential clinical adaptive value. The findings of this study enhance the understanding of heterogeneity among depressive disorders.
Subjects: Library Science，Information Science >> Information Science submitted time 2022-06-22
Abstract：
[Objective]Explore the combination path and key influencing factors of high propagation effect of rumor refuting information in social media environment.
[Methods] Based on the perspective of configuration, this paper obtained rumor dispelling data from Sina Weibo, explored the formation path of high communication effect by using fuzzy set qualitative comparative analysis (fsQCA) and further analyzed the key factors.
[Results]The results show that a total of four combined paths can produce high propagation effect, the overall coverage of all paths is about 46.1%, the original coverage of all paths is higher than the unique coverage, and the consistency level of the overall solution is higher than 0.8.
[Limitations] First of all, there are many factors that affect the spread effect of rumor refuting information, and this paper only considers some of them. Secondly, all the data in this study are from Sina Weibo, so it is difficult to determine whether the research conclusion can be applied to other social media.
[Conclusions]It is found that there are three modes (information-driven mode, agent-driven mode and collaborative driven mode) that produce high communication effect. Originality and richness of information are the key factors of high communication effect and play an indispensable role. In addition, the equivalence between configurations can also provide a theoretical explanation for the inconsistent research conclusions in the existing literature.
Peer Review Status:Awaiting Review
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