{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:E7P6RS27EF65GHKGE7VRH7KH62","short_pith_number":"pith:E7P6RS27","canonical_record":{"source":{"id":"1501.02905","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-01-13T08:09:16Z","cross_cats_sorted":[],"title_canon_sha256":"bae1da3d9845c05673a348d42c3daeec4251c4306bb872251aae7e6e34773c81","abstract_canon_sha256":"08f7c825137cda1441747412a37107de2fe359840337a36f526d443abcb43ae0"},"schema_version":"1.0"},"canonical_sha256":"27dfe8cb5f217dd31d4627eb13fd47f697aa0b2b18fb363326e05c0036def2d3","source":{"kind":"arxiv","id":"1501.02905","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1501.02905","created_at":"2026-05-18T01:24:08Z"},{"alias_kind":"arxiv_version","alias_value":"1501.02905v2","created_at":"2026-05-18T01:24:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1501.02905","created_at":"2026-05-18T01:24:08Z"},{"alias_kind":"pith_short_12","alias_value":"E7P6RS27EF65","created_at":"2026-05-18T12:29:19Z"},{"alias_kind":"pith_short_16","alias_value":"E7P6RS27EF65GHKG","created_at":"2026-05-18T12:29:19Z"},{"alias_kind":"pith_short_8","alias_value":"E7P6RS27","created_at":"2026-05-18T12:29:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:E7P6RS27EF65GHKGE7VRH7KH62","target":"record","payload":{"canonical_record":{"source":{"id":"1501.02905","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-01-13T08:09:16Z","cross_cats_sorted":[],"title_canon_sha256":"bae1da3d9845c05673a348d42c3daeec4251c4306bb872251aae7e6e34773c81","abstract_canon_sha256":"08f7c825137cda1441747412a37107de2fe359840337a36f526d443abcb43ae0"},"schema_version":"1.0"},"canonical_sha256":"27dfe8cb5f217dd31d4627eb13fd47f697aa0b2b18fb363326e05c0036def2d3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:24:08.729759Z","signature_b64":"Dji5vPWDEC38Cv2WbB6fgokXp9snhShAeHN/iJDPyUq6TenGEoCVEA44Oc6yRGztVbWOxjRQNlI0bNBTFnrTDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"27dfe8cb5f217dd31d4627eb13fd47f697aa0b2b18fb363326e05c0036def2d3","last_reissued_at":"2026-05-18T01:24:08.729041Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:24:08.729041Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1501.02905","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:24:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XKU3lRnJBnAs0qqGpajBoTpaCPF0q31STuAdcC0pa3iuE6McIT/Bw7FQPk0kd2+EhxRFKwNyfoF26aI5zpUEAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T09:24:21.726333Z"},"content_sha256":"cc7db9d40f4cf3141646a205f7cec73ae21eebd27fbc444ba9cbbfbbcd6ee9c3","schema_version":"1.0","event_id":"sha256:cc7db9d40f4cf3141646a205f7cec73ae21eebd27fbc444ba9cbbfbbcd6ee9c3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:E7P6RS27EF65GHKGE7VRH7KH62","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sampling Online Social Networks via Heterogeneous Statistics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Richard T. B. Ma, Xin Wang, Yinlong Xu, Zhipeng Li","submitted_at":"2015-01-13T08:09:16Z","abstract_excerpt":"Most sampling techniques for online social networks (OSNs) are based on a particular sampling method on a single graph, which is referred to as a statistics. However, various realizing methods on different graphs could possibly be used in the same OSN, and they may lead to different sampling efficiencies, i.e., asymptotic variances. To utilize multiple statistics for accurate measurements, we formulate a mixture sampling problem, through which we construct a mixture unbiased estimator which minimizes asymptotic variance. Given fixed sampling budgets for different statistics, we derive the opti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1501.02905","kind":"arxiv","version":2},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:24:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UvtlnIr+r4KjXwtOssEWPeD+I/zPsiOMUsCgFgu4PdEkhKC2IcltsEr/+HBSo4AqJIN5xVKnSwaJf3rD2A8pDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T09:24:21.726704Z"},"content_sha256":"460eb4c6617b9c4df8025c53d79d3a6a349d3f1fc06692590a361aca29a8b0e0","schema_version":"1.0","event_id":"sha256:460eb4c6617b9c4df8025c53d79d3a6a349d3f1fc06692590a361aca29a8b0e0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E7P6RS27EF65GHKGE7VRH7KH62/bundle.json","state_url":"https://pith.science/pith/E7P6RS27EF65GHKGE7VRH7KH62/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E7P6RS27EF65GHKGE7VRH7KH62/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-03T09:24:21Z","links":{"resolver":"https://pith.science/pith/E7P6RS27EF65GHKGE7VRH7KH62","bundle":"https://pith.science/pith/E7P6RS27EF65GHKGE7VRH7KH62/bundle.json","state":"https://pith.science/pith/E7P6RS27EF65GHKGE7VRH7KH62/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E7P6RS27EF65GHKGE7VRH7KH62/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:E7P6RS27EF65GHKGE7VRH7KH62","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"08f7c825137cda1441747412a37107de2fe359840337a36f526d443abcb43ae0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-01-13T08:09:16Z","title_canon_sha256":"bae1da3d9845c05673a348d42c3daeec4251c4306bb872251aae7e6e34773c81"},"schema_version":"1.0","source":{"id":"1501.02905","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1501.02905","created_at":"2026-05-18T01:24:08Z"},{"alias_kind":"arxiv_version","alias_value":"1501.02905v2","created_at":"2026-05-18T01:24:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1501.02905","created_at":"2026-05-18T01:24:08Z"},{"alias_kind":"pith_short_12","alias_value":"E7P6RS27EF65","created_at":"2026-05-18T12:29:19Z"},{"alias_kind":"pith_short_16","alias_value":"E7P6RS27EF65GHKG","created_at":"2026-05-18T12:29:19Z"},{"alias_kind":"pith_short_8","alias_value":"E7P6RS27","created_at":"2026-05-18T12:29:19Z"}],"graph_snapshots":[{"event_id":"sha256:460eb4c6617b9c4df8025c53d79d3a6a349d3f1fc06692590a361aca29a8b0e0","target":"graph","created_at":"2026-05-18T01:24:08Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Most sampling techniques for online social networks (OSNs) are based on a particular sampling method on a single graph, which is referred to as a statistics. However, various realizing methods on different graphs could possibly be used in the same OSN, and they may lead to different sampling efficiencies, i.e., asymptotic variances. To utilize multiple statistics for accurate measurements, we formulate a mixture sampling problem, through which we construct a mixture unbiased estimator which minimizes asymptotic variance. Given fixed sampling budgets for different statistics, we derive the opti","authors_text":"Richard T. B. Ma, Xin Wang, Yinlong Xu, Zhipeng Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-01-13T08:09:16Z","title":"Sampling Online Social Networks via Heterogeneous Statistics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1501.02905","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:cc7db9d40f4cf3141646a205f7cec73ae21eebd27fbc444ba9cbbfbbcd6ee9c3","target":"record","created_at":"2026-05-18T01:24:08Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"08f7c825137cda1441747412a37107de2fe359840337a36f526d443abcb43ae0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-01-13T08:09:16Z","title_canon_sha256":"bae1da3d9845c05673a348d42c3daeec4251c4306bb872251aae7e6e34773c81"},"schema_version":"1.0","source":{"id":"1501.02905","kind":"arxiv","version":2}},"canonical_sha256":"27dfe8cb5f217dd31d4627eb13fd47f697aa0b2b18fb363326e05c0036def2d3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"27dfe8cb5f217dd31d4627eb13fd47f697aa0b2b18fb363326e05c0036def2d3","first_computed_at":"2026-05-18T01:24:08.729041Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:24:08.729041Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Dji5vPWDEC38Cv2WbB6fgokXp9snhShAeHN/iJDPyUq6TenGEoCVEA44Oc6yRGztVbWOxjRQNlI0bNBTFnrTDg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:24:08.729759Z","signed_message":"canonical_sha256_bytes"},"source_id":"1501.02905","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cc7db9d40f4cf3141646a205f7cec73ae21eebd27fbc444ba9cbbfbbcd6ee9c3","sha256:460eb4c6617b9c4df8025c53d79d3a6a349d3f1fc06692590a361aca29a8b0e0"],"state_sha256":"22312b64c418049da16d7b83d270b149e549204e681e68f002875495544e7c2d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8nNFxnxM2+yuwAzCvFX6be0d0IPxjwYQm4C/7WziAsy07OdMV/538ZOmCkJDjRYu1PRADt18LEwjr4gc3JgUCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T09:24:21.728567Z","bundle_sha256":"3058b03d7bdd82294239811fc3b2ca6800ea2844067ac4d2feb070a4c90fe356"}}