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首页> 外文期刊>Advances in complex systems >INTERVENTIONS IN SOCIAL NETWORKS: IMPACT ON MOOD AND NETWORK DYNAMICS
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INTERVENTIONS IN SOCIAL NETWORKS: IMPACT ON MOOD AND NETWORK DYNAMICS

机译：社交网络中的干预：对情绪和网络动力学的影响

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Results from two studies on longitudinal friendship networks are presented, exploring the impact of a gratitude intervention on positive and negative affect dynamics in a social network. The gratitude intervention had been previously shown to increase positive affect and decrease negative affect in an individual but dynamic group effects have not been considered. In the first study, the intervention was administered to the whole network. In the second study, two social networks are considered and in each only a subset of individuals, initially low/high in negative affect respectively received the intervention as "agents of change". Data was analyzed using stochastic actor-based modeling techniques to identify resulting network changes, impact on positive and negative affect and potential contagion of mood within the group. The first study found a group level increase in positive and a decrease in negative affect. Homophily was detected with regard to positive and negative affect but no evidence of contagion was found. The network itself became more volatile along with a fall in rate of change of negative affect. Centrality measures indicated that the best broadcasters were the individuals with the least negative affect levels at the beginning of the study. In the second study, the positive and negative affect levels for the whole group depended on the initial levels of negative affect of the intervention recipients. There was evidence of positive affect contagion in the group where intervention recipients had low initial level of negative affect and contagion in negative affect for the group where recipients had initially high level of negative affect.
机译：提出了关于纵向友谊网络的两项研究的结果，探讨了感恩干预对社交网络中正面和负面影响动态的影响。先前已表明，感恩干预会增加个体的积极影响而减少负面影响，但尚未考虑动态的群体影响。在第一个研究中，将干预措施应用于整个网络。在第二项研究中，考虑了两个社交网络，并且在每个个体中，最初负面影响较低/较高的个体分别作为“变革的推动者”接受了干预。使用基于随机参与者的建模技术对数据进行分析，以识别产生的网络变化，对正面和负面影响的影响以及组内情绪的潜在传染。第一项研究发现，小组水平的积极影响增加而消极影响减少。检测到同质性有正面和负面影响，但没有发现传染的迹象。网络本身变得更加动荡，负面影响的变化率也随之下降。集中度测量表明，最佳广播机构是研究开始时负面影响程度最低的个体。在第二项研究中，整个组的正面和负面影响水平取决于干预接受者的负面影响的初始水平。有证据表明，在干预接受者最初具有较低的负面影响水平的人群中，有正向影响的传染，而对于接受者最初具有较高的负面影响水平的人群，具有负面影响的蔓延。

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