{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:BVG6BCMJY6JMBQYDD3LUQ3E627","short_pith_number":"pith:BVG6BCMJ","schema_version":"1.0","canonical_sha256":"0d4de08989c792c0c3031ed7486c9ed7c5ba0be801891ecb62d4301f3ca84816","source":{"kind":"arxiv","id":"1212.0884","version":5},"attestation_state":"computed","paper":{"title":"Maximizing Social Influence in Nearly Optimal Time","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI","physics.soc-ph"],"primary_cat":"cs.DS","authors_text":"Brendan Lucier, Christian Borgs, Jennifer Chayes, Michael Brautbar","submitted_at":"2012-12-04T21:53:07Z","abstract_excerpt":"Diffusion is a fundamental graph process, underpinning such phenomena as epidemic disease contagion and the spread of innovation by word-of-mouth. We address the algorithmic problem of finding a set of k initial seed nodes in a network so that the expected size of the resulting cascade is maximized, under the standard independent cascade model of network diffusion. Runtime is a primary consideration for this problem due to the massive size of the relevant input networks.\n  We provide a fast algorithm for the influence maximization problem, obtaining the near-optimal approximation factor of (1 "},"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":"1212.0884","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2012-12-04T21:53:07Z","cross_cats_sorted":["cs.SI","physics.soc-ph"],"title_canon_sha256":"b2697c8f6f2340544423c1bb32137acc9a6db13e17f44612608c3c4728fd8d58","abstract_canon_sha256":"e8a1e784539b52a8dc4702126b68d08dc12b20ffca1c293e54f1b1956a7cbf5c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:12:02.051190Z","signature_b64":"XCQ6xwB7Fz0AGBH5ckUQ4WwoIQ+lkvowMeHwR08EBgGXeRWQYPoKOVHlwtblhnmZNPvVn39NQlqKhkhDzNKJCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0d4de08989c792c0c3031ed7486c9ed7c5ba0be801891ecb62d4301f3ca84816","last_reissued_at":"2026-05-18T01:12:02.050800Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:12:02.050800Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Maximizing Social Influence in Nearly Optimal Time","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI","physics.soc-ph"],"primary_cat":"cs.DS","authors_text":"Brendan Lucier, Christian Borgs, Jennifer Chayes, Michael Brautbar","submitted_at":"2012-12-04T21:53:07Z","abstract_excerpt":"Diffusion is a fundamental graph process, underpinning such phenomena as epidemic disease contagion and the spread of innovation by word-of-mouth. We address the algorithmic problem of finding a set of k initial seed nodes in a network so that the expected size of the resulting cascade is maximized, under the standard independent cascade model of network diffusion. Runtime is a primary consideration for this problem due to the massive size of the relevant input networks.\n  We provide a fast algorithm for the influence maximization problem, obtaining the near-optimal approximation factor of (1 "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1212.0884","kind":"arxiv","version":5},"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":"1212.0884","created_at":"2026-05-18T01:12:02.050865+00:00"},{"alias_kind":"arxiv_version","alias_value":"1212.0884v5","created_at":"2026-05-18T01:12:02.050865+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1212.0884","created_at":"2026-05-18T01:12:02.050865+00:00"},{"alias_kind":"pith_short_12","alias_value":"BVG6BCMJY6JM","created_at":"2026-05-18T12:27:01.376967+00:00"},{"alias_kind":"pith_short_16","alias_value":"BVG6BCMJY6JMBQYD","created_at":"2026-05-18T12:27:01.376967+00:00"},{"alias_kind":"pith_short_8","alias_value":"BVG6BCMJ","created_at":"2026-05-18T12:27:01.376967+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/BVG6BCMJY6JMBQYDD3LUQ3E627","json":"https://pith.science/pith/BVG6BCMJY6JMBQYDD3LUQ3E627.json","graph_json":"https://pith.science/api/pith-number/BVG6BCMJY6JMBQYDD3LUQ3E627/graph.json","events_json":"https://pith.science/api/pith-number/BVG6BCMJY6JMBQYDD3LUQ3E627/events.json","paper":"https://pith.science/paper/BVG6BCMJ"},"agent_actions":{"view_html":"https://pith.science/pith/BVG6BCMJY6JMBQYDD3LUQ3E627","download_json":"https://pith.science/pith/BVG6BCMJY6JMBQYDD3LUQ3E627.json","view_paper":"https://pith.science/paper/BVG6BCMJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1212.0884&json=true","fetch_graph":"https://pith.science/api/pith-number/BVG6BCMJY6JMBQYDD3LUQ3E627/graph.json","fetch_events":"https://pith.science/api/pith-number/BVG6BCMJY6JMBQYDD3LUQ3E627/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BVG6BCMJY6JMBQYDD3LUQ3E627/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BVG6BCMJY6JMBQYDD3LUQ3E627/action/storage_attestation","attest_author":"https://pith.science/pith/BVG6BCMJY6JMBQYDD3LUQ3E627/action/author_attestation","sign_citation":"https://pith.science/pith/BVG6BCMJY6JMBQYDD3LUQ3E627/action/citation_signature","submit_replication":"https://pith.science/pith/BVG6BCMJY6JMBQYDD3LUQ3E627/action/replication_record"}},"created_at":"2026-05-18T01:12:02.050865+00:00","updated_at":"2026-05-18T01:12:02.050865+00:00"}