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) en Exploring the gravitational model for ranking influential nodes in directed acyclic networks
f | 1 | { | f | 1 | { |
2 | "author": "Alberto Garc\u00eda Robledo", | 2 | "author": "Alberto Garc\u00eda Robledo", | ||
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18 | "metadata_created": "2025-08-04T23:52:36.704906", | 18 | "metadata_created": "2025-08-04T23:52:36.704906", | ||
t | 19 | "metadata_modified": "2025-08-04T23:55:20.932740", | t | 19 | "metadata_modified": "2025-08-04T23:58:00.851582", |
20 | "name": | 20 | "name": | ||
21 | nal-model-for-ranking-influential-nodes-in-directed-acyclic-networks", | 21 | nal-model-for-ranking-influential-nodes-in-directed-acyclic-networks", | ||
22 | "notes": "In Social Network Analysis (SNA), the application of | 22 | "notes": "In Social Network Analysis (SNA), the application of | ||
23 | Directed Acyclic Graphs (DAGs) provides unique opportunities to | 23 | Directed Acyclic Graphs (DAGs) provides unique opportunities to | ||
24 | explore structures where relationships have direction and do not form | 24 | explore structures where relationships have direction and do not form | ||
25 | cycles, such as citation networks and organizational hierarchies. | 25 | cycles, such as citation networks and organizational hierarchies. | ||
26 | Recently, the gravitational model has gained recognition as an | 26 | Recently, the gravitational model has gained recognition as an | ||
27 | effective method for identifying influential spreaders within complex | 27 | effective method for identifying influential spreaders within complex | ||
28 | networks, a problem of relevance in SNA. While there have been | 28 | networks, a problem of relevance in SNA. While there have been | ||
29 | numerous investigations into the gravitational model in undirected and | 29 | numerous investigations into the gravitational model in undirected and | ||
30 | cyclic graphs, the unique challenges and dynamics associated with DAGs | 30 | cyclic graphs, the unique challenges and dynamics associated with DAGs | ||
31 | have yet to be fully explored. In this study, we conduct a | 31 | have yet to be fully explored. In this study, we conduct a | ||
32 | comprehensive analysis of the gravitational model for ranking nodes in | 32 | comprehensive analysis of the gravitational model for ranking nodes in | ||
33 | DAGs. First, we introduce an efficient linear-time algorithm | 33 | DAGs. First, we introduce an efficient linear-time algorithm | ||
34 | specifically designed to compute the gravitational index of nodes in | 34 | specifically designed to compute the gravitational index of nodes in | ||
35 | large-scale DAGs. Next, using thousands of synthetic and empirical | 35 | large-scale DAGs. Next, using thousands of synthetic and empirical | ||
36 | DAGs, we compare the impact of the gravitational index on the accuracy | 36 | DAGs, we compare the impact of the gravitational index on the accuracy | ||
37 | and resolution of node rankings across different mass indexes. We then | 37 | and resolution of node rankings across different mass indexes. We then | ||
38 | examine how DAG structural properties influence the monotonicity of | 38 | examine how DAG structural properties influence the monotonicity of | ||
39 | node rankings, with a particular focus on the k-shell index. We find | 39 | node rankings, with a particular focus on the k-shell index. We find | ||
40 | that, in DAGs, the gravitational formula effectively enhances the | 40 | that, in DAGs, the gravitational formula effectively enhances the | ||
41 | monotonicity of k-shell centrality, though it is less effective for | 41 | monotonicity of k-shell centrality, though it is less effective for | ||
42 | other types of centrality indexes. We also find that smaller, shorter, | 42 | other types of centrality indexes. We also find that smaller, shorter, | ||
43 | and highly centralized DAGs exhibit low ranking resolution across all | 43 | and highly centralized DAGs exhibit low ranking resolution across all | ||
44 | centrality indexes examined in this study, including the gravity-based | 44 | centrality indexes examined in this study, including the gravity-based | ||
45 | ones. Despite this challenge, our results demonstrate that the | 45 | ones. Despite this challenge, our results demonstrate that the | ||
46 | application of gravity-based models improves the ranking accuracy of | 46 | application of gravity-based models improves the ranking accuracy of | ||
47 | several centrality measures across most of the studied DAG datasets.", | 47 | several centrality measures across most of the studied DAG datasets.", | ||
48 | "num_resources": 1, | 48 | "num_resources": 1, | ||
49 | "num_tags": 1, | 49 | "num_tags": 1, | ||
50 | "organization": { | 50 | "organization": { | ||
51 | "approval_status": "approved", | 51 | "approval_status": "approved", | ||
52 | "created": "2022-05-19T00:10:30.480393", | 52 | "created": "2022-05-19T00:10:30.480393", | ||
53 | "description": "Observatorio Metropolitano CentroGeo", | 53 | "description": "Observatorio Metropolitano CentroGeo", | ||
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55 | "image_url": | 55 | "image_url": | ||
56 | "2022-05-19-001030.456616FullColor1280x1024LogoOnly.png", | 56 | "2022-05-19-001030.456616FullColor1280x1024LogoOnly.png", | ||
57 | "is_organization": true, | 57 | "is_organization": true, | ||
58 | "name": "observatorio-metropolitano-centrogeo", | 58 | "name": "observatorio-metropolitano-centrogeo", | ||
59 | "state": "active", | 59 | "state": "active", | ||
60 | "title": "Observatorio Metropolitano CentroGeo", | 60 | "title": "Observatorio Metropolitano CentroGeo", | ||
61 | "type": "organization" | 61 | "type": "organization" | ||
62 | }, | 62 | }, | ||
63 | "owner_org": "b3b3a79d-748a-4464-9471-732b6c74ec53", | 63 | "owner_org": "b3b3a79d-748a-4464-9471-732b6c74ec53", | ||
64 | "private": false, | 64 | "private": false, | ||
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81 | "name": "DOI", | 81 | "name": "DOI", | ||
82 | "package_id": "b54636b8-f731-4de9-8c3d-0892231bbe14", | 82 | "package_id": "b54636b8-f731-4de9-8c3d-0892231bbe14", | ||
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86 | "state": "active", | 86 | "state": "active", | ||
87 | "url": "https://doi.org/10.1007/s13278-025-01500-4", | 87 | "url": "https://doi.org/10.1007/s13278-025-01500-4", | ||
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89 | } | 89 | } | ||
90 | ], | 90 | ], | ||
91 | "state": "active", | 91 | "state": "active", | ||
92 | "tags": [ | 92 | "tags": [ | ||
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98 | "vocabulary_id": null | 98 | "vocabulary_id": null | ||
99 | } | 99 | } | ||
100 | ], | 100 | ], | ||
101 | "title": "Exploring the gravitational model for ranking influential | 101 | "title": "Exploring the gravitational model for ranking influential | ||
102 | nodes in directed acyclic networks", | 102 | nodes in directed acyclic networks", | ||
103 | "type": "dataset", | 103 | "type": "dataset", | ||
104 | "url": "https://doi.org/10.1007/s13278-025-01500-4", | 104 | "url": "https://doi.org/10.1007/s13278-025-01500-4", | ||
105 | "version": "1.0" | 105 | "version": "1.0" | ||
106 | } | 106 | } |