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
It is difficult to attract FDI into western China.This situation might not be explained by traditional geographical factors,because the gap of inward FDI between the western and the eastern regions of China has increa...It is difficult to attract FDI into western China.This situation might not be explained by traditional geographical factors,because the gap of inward FDI between the western and the eastern regions of China has increased.This paper attempts to explain the situation from an industrial perspective by exploring the industrial differences in the two regions and analyzing their effects in terms of industrial development level,industrial structure and industrial linking capability.The results reveal that industrial factors are important barriers to the inflow of FDI to western China.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It is difficult to attract FDI into western China.This situation might not be explained by traditional geographical factors,because the gap of inward FDI between the western and the eastern regions of China has increased.This paper attempts to explain the situation from an industrial perspective by exploring the industrial differences in the two regions and analyzing their effects in terms of industrial development level,industrial structure and industrial linking capability.The results reveal that industrial factors are important barriers to the inflow of FDI to western China.
