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
Social capital has played an increasingly important role in regional development.China is a country with high stocks of social capital.Using several different indicators of social capital,this study tries to research ...Social capital has played an increasingly important role in regional development.China is a country with high stocks of social capital.Using several different indicators of social capital,this study tries to research the regional disparities in social capital and the influence of social capital on economic growth of China in 1978-2004.Measuring social capital with indicators of associations,charities and blood donation rates,this study finds significant regional disparities in social capital at provincial level in China.Those indicators for social capital are highly correlated with regional economic performance.Statistical analysis shows that social capital has a significant and positive effect on a long-term provincial economic growth.This relationship exists after controlling policy,macro location factors,and per capita GDP in the initial year.The empirical findings indicate that institutions,culture and social relations are critical for regional development in China.Therefore,the creation and support of social capital should be paid more attention to when making regional policy.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.
基金Under the auspices of National Natural Science Foundation of China(No.40871065,40830747)
文摘Social capital has played an increasingly important role in regional development.China is a country with high stocks of social capital.Using several different indicators of social capital,this study tries to research the regional disparities in social capital and the influence of social capital on economic growth of China in 1978-2004.Measuring social capital with indicators of associations,charities and blood donation rates,this study finds significant regional disparities in social capital at provincial level in China.Those indicators for social capital are highly correlated with regional economic performance.Statistical analysis shows that social capital has a significant and positive effect on a long-term provincial economic growth.This relationship exists after controlling policy,macro location factors,and per capita GDP in the initial year.The empirical findings indicate that institutions,culture and social relations are critical for regional development in China.Therefore,the creation and support of social capital should be paid more attention to when making regional policy.
