{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2010:EDEPA5UEUZ4ESTFNMQYCKQFRVH","short_pith_number":"pith:EDEPA5UE","schema_version":"1.0","canonical_sha256":"20c8f07684a678494cad64302540b1a9f9e45bc877d5b32bd60c3b842de2477b","source":{"kind":"arxiv","id":"1005.4093","version":1},"attestation_state":"computed","paper":{"title":"On the Efficiency of Data Representation on the Modeling and Characterization of Complex Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.comp-ph","authors_text":"Carlos A. Ruggiero, Gonzalo Travieso, Luciano da Fontoura Costa, Odemir M. Bruno","submitted_at":"2010-05-21T22:38:59Z","abstract_excerpt":"Specific choices about how to represent complex networks can have a substantial effect on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically as matrices or dynamically as spase structures. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1005.4093","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.comp-ph","submitted_at":"2010-05-21T22:38:59Z","cross_cats_sorted":[],"title_canon_sha256":"027dc837bfdd3a3af97c01318609bb1f73367c5a60b98762739625133ae67a7c","abstract_canon_sha256":"24c823becbffa9e57668925345fcc80735cbef96e5292f3715dde078e1d37679"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:07:15.511957Z","signature_b64":"RRneoqWRQvQ3z2XSuP0MgawlMgD+PD4JEjJ2p95EYn/e5v10TRmwJugnliSCW4FrGAvflLS/sX1yfBFo+dtiAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"20c8f07684a678494cad64302540b1a9f9e45bc877d5b32bd60c3b842de2477b","last_reissued_at":"2026-05-18T02:07:15.511304Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:07:15.511304Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"On the Efficiency of Data Representation on the Modeling and Characterization of Complex Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.comp-ph","authors_text":"Carlos A. Ruggiero, Gonzalo Travieso, Luciano da Fontoura Costa, Odemir M. Bruno","submitted_at":"2010-05-21T22:38:59Z","abstract_excerpt":"Specific choices about how to represent complex networks can have a substantial effect on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically as matrices or dynamically as spase structures. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1005.4093","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1005.4093","created_at":"2026-05-18T02:07:15.511425+00:00"},{"alias_kind":"arxiv_version","alias_value":"1005.4093v1","created_at":"2026-05-18T02:07:15.511425+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1005.4093","created_at":"2026-05-18T02:07:15.511425+00:00"},{"alias_kind":"pith_short_12","alias_value":"EDEPA5UEUZ4E","created_at":"2026-05-18T12:26:06.534383+00:00"},{"alias_kind":"pith_short_16","alias_value":"EDEPA5UEUZ4ESTFN","created_at":"2026-05-18T12:26:06.534383+00:00"},{"alias_kind":"pith_short_8","alias_value":"EDEPA5UE","created_at":"2026-05-18T12:26:06.534383+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/EDEPA5UEUZ4ESTFNMQYCKQFRVH","json":"https://pith.science/pith/EDEPA5UEUZ4ESTFNMQYCKQFRVH.json","graph_json":"https://pith.science/api/pith-number/EDEPA5UEUZ4ESTFNMQYCKQFRVH/graph.json","events_json":"https://pith.science/api/pith-number/EDEPA5UEUZ4ESTFNMQYCKQFRVH/events.json","paper":"https://pith.science/paper/EDEPA5UE"},"agent_actions":{"view_html":"https://pith.science/pith/EDEPA5UEUZ4ESTFNMQYCKQFRVH","download_json":"https://pith.science/pith/EDEPA5UEUZ4ESTFNMQYCKQFRVH.json","view_paper":"https://pith.science/paper/EDEPA5UE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1005.4093&json=true","fetch_graph":"https://pith.science/api/pith-number/EDEPA5UEUZ4ESTFNMQYCKQFRVH/graph.json","fetch_events":"https://pith.science/api/pith-number/EDEPA5UEUZ4ESTFNMQYCKQFRVH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EDEPA5UEUZ4ESTFNMQYCKQFRVH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EDEPA5UEUZ4ESTFNMQYCKQFRVH/action/storage_attestation","attest_author":"https://pith.science/pith/EDEPA5UEUZ4ESTFNMQYCKQFRVH/action/author_attestation","sign_citation":"https://pith.science/pith/EDEPA5UEUZ4ESTFNMQYCKQFRVH/action/citation_signature","submit_replication":"https://pith.science/pith/EDEPA5UEUZ4ESTFNMQYCKQFRVH/action/replication_record"}},"created_at":"2026-05-18T02:07:15.511425+00:00","updated_at":"2026-05-18T02:07:15.511425+00:00"}