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En el instante 10 de octubre de 2025, 7:19:34 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
f | 1 | { | f | 1 | { |
2 | "author": "A Garcia-Robledo, M Zangiabady, J Sonneveld", | 2 | "author": "A Garcia-Robledo, M Zangiabady, J Sonneveld", | ||
3 | "author_email": null, | 3 | "author_email": null, | ||
4 | "creator_user_id": "a3da3ec9-3fd4-47a4-8d04-0a90b09614e0", | 4 | "creator_user_id": "a3da3ec9-3fd4-47a4-8d04-0a90b09614e0", | ||
5 | "extras": [ | 5 | "extras": [ | ||
6 | { | 6 | { | ||
7 | "key": "Publicaci\u00f3n", | 7 | "key": "Publicaci\u00f3n", | ||
8 | "value": "Revista" | 8 | "value": "Revista" | ||
9 | }, | 9 | }, | ||
10 | { | 10 | { | ||
11 | "key": "Tipo", | 11 | "key": "Tipo", | ||
12 | "value": "Publicaci\u00f3n" | 12 | "value": "Publicaci\u00f3n" | ||
13 | } | 13 | } | ||
14 | ], | 14 | ], | ||
15 | "groups": [ | 15 | "groups": [ | ||
16 | { | 16 | { | ||
17 | "description": "Este grupo integra las publicaciones | 17 | "description": "Este grupo integra las publicaciones | ||
18 | acad\u00e9micas derivadas de los proyectos de investigaci\u00f3n del | 18 | acad\u00e9micas derivadas de los proyectos de investigaci\u00f3n del | ||
19 | Observatorio Metropolitano CentroGeo. Incluye art\u00edculos | 19 | Observatorio Metropolitano CentroGeo. Incluye art\u00edculos | ||
20 | presentados en congresos nacionales e internacionales, manuscritos en | 20 | presentados en congresos nacionales e internacionales, manuscritos en | ||
21 | formato preprint, cap\u00edtulos de libro y trabajos publicados en | 21 | formato preprint, cap\u00edtulos de libro y trabajos publicados en | ||
22 | revistas cient\u00edficas especializadas. Estos materiales reflejan la | 22 | revistas cient\u00edficas especializadas. Estos materiales reflejan la | ||
23 | labor de investigaci\u00f3n, desarrollo metodol\u00f3gico y | 23 | labor de investigaci\u00f3n, desarrollo metodol\u00f3gico y | ||
24 | an\u00e1lisis territorial del observatorio, contribuyendo al avance | 24 | an\u00e1lisis territorial del observatorio, contribuyendo al avance | ||
25 | del conocimiento en temas urbanos, metropolitanos y geoespaciales.", | 25 | del conocimiento en temas urbanos, metropolitanos y geoespaciales.", | ||
26 | "display_name": "Publicaciones", | 26 | "display_name": "Publicaciones", | ||
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29 | "name": "publicaciones", | 29 | "name": "publicaciones", | ||
30 | "title": "Publicaciones" | 30 | "title": "Publicaciones" | ||
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39 | "metadata_created": "2025-10-10T07:19:33.796781", | 39 | "metadata_created": "2025-10-10T07:19:33.796781", | ||
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41 | "name": | 41 | "name": | ||
42 | l-for-ranking-influential-nodes-in-directed-acyclic-net-7b47ef9d5d86", | 42 | l-for-ranking-influential-nodes-in-directed-acyclic-net-7b47ef9d5d86", | ||
43 | "notes": "In Social Network Analysis (SNA), the application of | 43 | "notes": "In Social Network Analysis (SNA), the application of | ||
44 | Directed Acyclic Graphs (DAGs) provides unique opportunities to | 44 | Directed Acyclic Graphs (DAGs) provides unique opportunities to | ||
45 | explore structures where relationships have direction and do not form | 45 | explore structures where relationships have direction and do not form | ||
46 | cycles, such as citation networks and organizational hierarchies. | 46 | cycles, such as citation networks and organizational hierarchies. | ||
47 | Recently, the gravitational model has gained recognition as an | 47 | Recently, the gravitational model has gained recognition as an | ||
48 | effective method for identifying influential spreaders within complex | 48 | effective method for identifying influential spreaders within complex | ||
49 | networks, a problem of relevance in SNA. While there have been | 49 | networks, a problem of relevance in SNA. While there have been | ||
50 | numerous investigations into the gravitational model in undirected and | 50 | numerous investigations into the gravitational model in undirected and | ||
51 | cyclic graphs, the unique challenges and dynamics associated with DAGs | 51 | cyclic graphs, the unique challenges and dynamics associated with DAGs | ||
52 | have yet to be fully explored. In this study, we conduct a | 52 | have yet to be fully explored. In this study, we conduct a | ||
53 | comprehensive analysis of the gravitational model for ranking nodes in | 53 | comprehensive analysis of the gravitational model for ranking nodes in | ||
54 | DAGs. First, we introduce an efficient linear-time algorithm | 54 | DAGs. First, we introduce an efficient linear-time algorithm | ||
55 | specifically designed to compute the gravitational index of nodes in | 55 | specifically designed to compute the gravitational index of nodes in | ||
56 | large-scale DAGs. Next, using thousands of synthetic and empirical | 56 | large-scale DAGs. Next, using thousands of synthetic and empirical | ||
57 | DAGs, we compare the impact of the gravitational index on the accuracy | 57 | DAGs, we compare the impact of the gravitational index on the accuracy | ||
58 | and resolution of node rankings across different mass indexes. We then | 58 | and resolution of node rankings across different mass indexes. We then | ||
59 | examine how DAG structural properties influence the monotonicity of | 59 | examine how DAG structural properties influence the monotonicity of | ||
60 | node rankings, with a particular focus on the k-shell index. We find | 60 | node rankings, with a particular focus on the k-shell index. We find | ||
61 | that, in DAGs, the gravitational formula effectively enhances the | 61 | that, in DAGs, the gravitational formula effectively enhances the | ||
62 | monotonicity of k-shell centrality, though it is less effective for | 62 | monotonicity of k-shell centrality, though it is less effective for | ||
63 | other types of centrality indexes. We also find that smaller, shorter, | 63 | other types of centrality indexes. We also find that smaller, shorter, | ||
64 | and highly centralized DAGs exhibit low ranking resolution across all | 64 | and highly centralized DAGs exhibit low ranking resolution across all | ||
65 | centrality indexes examined in this study, including the gravity-based | 65 | centrality indexes examined in this study, including the gravity-based | ||
66 | ones. Despite this challenge, our results demonstrate that the | 66 | ones. Despite this challenge, our results demonstrate that the | ||
67 | application of gravity-based models improves the ranking accuracy of | 67 | application of gravity-based models improves the ranking accuracy of | ||
68 | several centrality measures across most of the studied DAG datasets.", | 68 | several centrality measures across most of the studied DAG datasets.", | ||
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72 | "approval_status": "approved", | 72 | "approval_status": "approved", | ||
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95 | application of Directed Acyclic Graphs (DAGs) provides unique | ||||
96 | opportunities to explore structures where relationships have direction | ||||
97 | and do not form cycles, such as citation networks and organizational | ||||
98 | hierarchies. Recently, the gravitational model has gained recognition | ||||
99 | as an effective method for identifying influential spreaders within | ||||
100 | complex networks, a problem of relevance in SNA. While there have been | ||||
101 | numerous investigations into the gravitational model in undirected and | ||||
102 | cyclic graphs, the unique challenges and dynamics associated with DAGs | ||||
103 | have yet to be fully explored. In this study, we conduct a | ||||
104 | comprehensive analysis of the gravitational model for ranking nodes in | ||||
105 | DAGs. First, we introduce an efficient linear-time algorithm | ||||
106 | specifically designed to compute the gravitational index of nodes in | ||||
107 | large-scale DAGs. Next, using thousands of synthetic and empirical | ||||
108 | DAGs, we compare the impact of the gravitational index on the accuracy | ||||
109 | and resolution of node rankings across different mass indexes. We then | ||||
110 | examine how DAG structural properties influence the monotonicity of | ||||
111 | node rankings, with a particular focus on the k-shell index. We find | ||||
112 | that, in DAGs, the gravitational formula effectively enhances the | ||||
113 | monotonicity of k-shell centrality, though it is less effective for | ||||
114 | other types of centrality indexes. We also find that smaller, shorter, | ||||
115 | and highly centralized DAGs exhibit low ranking resolution across all | ||||
116 | centrality indexes examined in this study, including the gravity-based | ||||
117 | ones. Despite this challenge, our results demonstrate that the | ||||
118 | application of gravity-based models improves the ranking accuracy of | ||||
119 | several centrality measures across most of the studied DAG datasets.", | ||||
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127 | "name": "Exploring the gravitational model for ranking | ||||
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127 | "title": "Exploring the gravitational model for ranking influential | 176 | "title": "Exploring the gravitational model for ranking influential | ||
128 | nodes in directed acyclic networks", | 177 | nodes in directed acyclic networks", | ||
129 | "type": "dataset", | 178 | "type": "dataset", | ||
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