Social networks like Facebook, X (Twitter), and LinkedIn provide an interaction and communication environment for users to generate and share content, allowing for the observation of social behaviours in the digital w...Social networks like Facebook, X (Twitter), and LinkedIn provide an interaction and communication environment for users to generate and share content, allowing for the observation of social behaviours in the digital world. These networks can be viewed as a collection of nodes and edges, where users and their interactions are represented as nodes and the connections between them as edges. Understanding the factors that contribute to the formation of these edges is important for studying network structure and processes. This knowledge can be applied to various areas such as identifying communities, recommending friends, and targeting online advertisements. Several factors, including node popularity and friends-of-friends relationships, influence edge formation and network growth. This research focuses on the temporal activity of nodes and its impact on edge formation. Specifically, the study examines how the minimum age of friends-of-friends edges and the average age of all edges connected to potential target nodes influence the formation of network edges. Discrete choice analysis is used to analyse the combined effect of these temporal factors and other well-known attributes like node degree (i.e., the number of connections a node has) and network distance between nodes. The findings reveal that temporal properties have a similar impact as network proximity in predicting the creation of links. By incorporating temporal features into the models, the accuracy of link prediction can be further improved.展开更多
目的探讨急诊重症监护室(emergency intensive care unit,EICU)住院患者家属创伤后成长的影响因素及其与社会支持水平的相关性。方法选择2020年6月—2023年6月南通大学附属医院EICU 80名住院患者的家属作为研究对象。采用创伤后成长评...目的探讨急诊重症监护室(emergency intensive care unit,EICU)住院患者家属创伤后成长的影响因素及其与社会支持水平的相关性。方法选择2020年6月—2023年6月南通大学附属医院EICU 80名住院患者的家属作为研究对象。采用创伤后成长评定量表以及社会支持评定量表评价EICU住院患者家属创伤后成长水平及社会支持水平。分析患者家属创伤后成长水平与社会支持水平的相关性,并对患者家属创伤后成长水平的影响因素进行单因素、多因素logistic回归分析。结果80名EICU住院患者家属创伤后成长水平评分为(60.53±13.02)分,其中得分最高维度为与他人关系,其次为个人力量。经单因素分析可见,患者家属不同性别、学历、与患者关系、急性生理学和慢性健康状况评价Ⅱ(acute physiology and chronic health evaluationⅡ,APACHEⅡ)评分的创伤后成长水平评分比较,差异有统计学意义(P<0.05)。家属社会支持水平评分均低于国内常模(P<0.05)。经Pearson相关性分析,EICU住院患者家属创伤后成长水平与社会支持水平呈正相关(P<0.05)。经多因素分析可见,性别、学历、患者APACHEⅡ评分与社会支持水平是ICU住院患者家属创伤后成长的独立影响因素(P<0.05)。结论性别、学历、患者APACHEⅡ评分与社会支持水平是EICU住院患者家属创伤后成长的影响因素,临床应增强对患者家属关注度,积极鼓励家属缓解负面情绪,提升创伤后成长水平。展开更多
文摘Social networks like Facebook, X (Twitter), and LinkedIn provide an interaction and communication environment for users to generate and share content, allowing for the observation of social behaviours in the digital world. These networks can be viewed as a collection of nodes and edges, where users and their interactions are represented as nodes and the connections between them as edges. Understanding the factors that contribute to the formation of these edges is important for studying network structure and processes. This knowledge can be applied to various areas such as identifying communities, recommending friends, and targeting online advertisements. Several factors, including node popularity and friends-of-friends relationships, influence edge formation and network growth. This research focuses on the temporal activity of nodes and its impact on edge formation. Specifically, the study examines how the minimum age of friends-of-friends edges and the average age of all edges connected to potential target nodes influence the formation of network edges. Discrete choice analysis is used to analyse the combined effect of these temporal factors and other well-known attributes like node degree (i.e., the number of connections a node has) and network distance between nodes. The findings reveal that temporal properties have a similar impact as network proximity in predicting the creation of links. By incorporating temporal features into the models, the accuracy of link prediction can be further improved.
文摘目的探讨急诊重症监护室(emergency intensive care unit,EICU)住院患者家属创伤后成长的影响因素及其与社会支持水平的相关性。方法选择2020年6月—2023年6月南通大学附属医院EICU 80名住院患者的家属作为研究对象。采用创伤后成长评定量表以及社会支持评定量表评价EICU住院患者家属创伤后成长水平及社会支持水平。分析患者家属创伤后成长水平与社会支持水平的相关性,并对患者家属创伤后成长水平的影响因素进行单因素、多因素logistic回归分析。结果80名EICU住院患者家属创伤后成长水平评分为(60.53±13.02)分,其中得分最高维度为与他人关系,其次为个人力量。经单因素分析可见,患者家属不同性别、学历、与患者关系、急性生理学和慢性健康状况评价Ⅱ(acute physiology and chronic health evaluationⅡ,APACHEⅡ)评分的创伤后成长水平评分比较,差异有统计学意义(P<0.05)。家属社会支持水平评分均低于国内常模(P<0.05)。经Pearson相关性分析,EICU住院患者家属创伤后成长水平与社会支持水平呈正相关(P<0.05)。经多因素分析可见,性别、学历、患者APACHEⅡ评分与社会支持水平是ICU住院患者家属创伤后成长的独立影响因素(P<0.05)。结论性别、学历、患者APACHEⅡ评分与社会支持水平是EICU住院患者家属创伤后成长的影响因素,临床应增强对患者家属关注度,积极鼓励家属缓解负面情绪,提升创伤后成长水平。
