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En el instante 21 de octubre de 2025, 8:59:04 UTC,
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Añadido recurso Exploring the gravitational model for ranking influential nodes in directed acyclic networks a Exploring the gravitational model for ranking influential nodes in directed acyclic networks
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| 2 | "author": "A Garcia-Robledo, M Zangiabady, J Sonneveld", | 2 | "author": "A Garcia-Robledo, M Zangiabady, J Sonneveld", | ||
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| 38 | "https://link.springer.com/article/10.1007/s13278-025-01500-4" | 38 | "https://link.springer.com/article/10.1007/s13278-025-01500-4" | ||
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| 60 | "notes": "In Social Network Analysis (SNA), the application of | 60 | "notes": "In Social Network Analysis (SNA), the application of | ||
| 61 | Directed Acyclic Graphs (DAGs) provides unique opportunities to | 61 | Directed Acyclic Graphs (DAGs) provides unique opportunities to | ||
| 62 | explore structures where relationships have direction and do not form | 62 | explore structures where relationships have direction and do not form | ||
| 63 | cycles, such as citation networks and organizational hierarchies. | 63 | cycles, such as citation networks and organizational hierarchies. | ||
| 64 | Recently, the gravitational model has gained recognition as an | 64 | Recently, the gravitational model has gained recognition as an | ||
| 65 | effective method for identifying influential spreaders within complex | 65 | effective method for identifying influential spreaders within complex | ||
| 66 | networks, a problem of relevance in SNA. While there have been | 66 | networks, a problem of relevance in SNA. While there have been | ||
| 67 | numerous investigations into the gravitational model in undirected and | 67 | numerous investigations into the gravitational model in undirected and | ||
| 68 | cyclic graphs, the unique challenges and dynamics associated with DAGs | 68 | cyclic graphs, the unique challenges and dynamics associated with DAGs | ||
| 69 | have yet to be fully explored. In this study, we conduct a | 69 | have yet to be fully explored. In this study, we conduct a | ||
| 70 | comprehensive analysis of the gravitational model for ranking nodes in | 70 | comprehensive analysis of the gravitational model for ranking nodes in | ||
| 71 | DAGs. First, we introduce an efficient linear-time algorithm | 71 | DAGs. First, we introduce an efficient linear-time algorithm | ||
| 72 | specifically designed to compute the gravitational index of nodes in | 72 | specifically designed to compute the gravitational index of nodes in | ||
| 73 | large-scale DAGs. Next, using thousands of synthetic and empirical | 73 | large-scale DAGs. Next, using thousands of synthetic and empirical | ||
| 74 | DAGs, we compare the impact of the gravitational index on the accuracy | 74 | DAGs, we compare the impact of the gravitational index on the accuracy | ||
| 75 | and resolution of node rankings across different mass indexes. We then | 75 | and resolution of node rankings across different mass indexes. We then | ||
| 76 | examine how DAG structural properties influence the monotonicity of | 76 | examine how DAG structural properties influence the monotonicity of | ||
| 77 | node rankings, with a particular focus on the k-shell index. We find | 77 | node rankings, with a particular focus on the k-shell index. We find | ||
| 78 | that, in DAGs, the gravitational formula effectively enhances the | 78 | that, in DAGs, the gravitational formula effectively enhances the | ||
| 79 | monotonicity of k-shell centrality, though it is less effective for | 79 | monotonicity of k-shell centrality, though it is less effective for | ||
| 80 | other types of centrality indexes. We also find that smaller, shorter, | 80 | other types of centrality indexes. We also find that smaller, shorter, | ||
| 81 | and highly centralized DAGs exhibit low ranking resolution across all | 81 | and highly centralized DAGs exhibit low ranking resolution across all | ||
| 82 | centrality indexes examined in this study, including the gravity-based | 82 | centrality indexes examined in this study, including the gravity-based | ||
| 83 | ones. Despite this challenge, our results demonstrate that the | 83 | ones. Despite this challenge, our results demonstrate that the | ||
| 84 | application of gravity-based models improves the ranking accuracy of | 84 | application of gravity-based models improves the ranking accuracy of | ||
| 85 | several centrality measures across most of the studied DAG datasets.", | 85 | several centrality measures across most of the studied DAG datasets.", | ||
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| 112 | application of Directed Acyclic Graphs (DAGs) provides unique | ||||
| 113 | opportunities to explore structures where relationships have direction | ||||
| 114 | and do not form cycles, such as citation networks and organizational | ||||
| 115 | hierarchies. Recently, the gravitational model has gained recognition | ||||
| 116 | as an effective method for identifying influential spreaders within | ||||
| 117 | complex networks, a problem of relevance in SNA. While there have been | ||||
| 118 | numerous investigations into the gravitational model in undirected and | ||||
| 119 | cyclic graphs, the unique challenges and dynamics associated with DAGs | ||||
| 120 | have yet to be fully explored. In this study, we conduct a | ||||
| 121 | comprehensive analysis of the gravitational model for ranking nodes in | ||||
| 122 | DAGs. First, we introduce an efficient linear-time algorithm | ||||
| 123 | specifically designed to compute the gravitational index of nodes in | ||||
| 124 | large-scale DAGs. Next, using thousands of synthetic and empirical | ||||
| 125 | DAGs, we compare the impact of the gravitational index on the accuracy | ||||
| 126 | and resolution of node rankings across different mass indexes. We then | ||||
| 127 | examine how DAG structural properties influence the monotonicity of | ||||
| 128 | node rankings, with a particular focus on the k-shell index. We find | ||||
| 129 | that, in DAGs, the gravitational formula effectively enhances the | ||||
| 130 | monotonicity of k-shell centrality, though it is less effective for | ||||
| 131 | other types of centrality indexes. We also find that smaller, shorter, | ||||
| 132 | and highly centralized DAGs exhibit low ranking resolution across all | ||||
| 133 | centrality indexes examined in this study, including the gravity-based | ||||
| 134 | ones. Despite this challenge, our results demonstrate that the | ||||
| 135 | application of gravity-based models improves the ranking accuracy of | ||||
| 136 | several centrality measures across most of the studied DAG datasets.", | ||||
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| 144 | "name": "Exploring the gravitational model for ranking | ||||
| 145 | influential nodes in directed acyclic networks", | ||||
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| 123 | "title": "Exploring the gravitational model for ranking influential | 173 | "title": "Exploring the gravitational model for ranking influential | ||
| 124 | nodes in directed acyclic networks", | 174 | nodes in directed acyclic networks", | ||
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