{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:WSZVQKQ7JY4JC2XQ7GH2PT43YL","short_pith_number":"pith:WSZVQKQ7","canonical_record":{"source":{"id":"1902.03097","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2019-01-29T11:57:53Z","cross_cats_sorted":["cs.LG","stat.AP","stat.ML"],"title_canon_sha256":"b0f43e064722e5f6bcaf3849fa950b83f830a7447ffe5846c1904d6e1ee2e71a","abstract_canon_sha256":"704924e679976843d45c35d57bdfe3362621e437328b2a7341a95482866e5c61"},"schema_version":"1.0"},"canonical_sha256":"b4b3582a1f4e38916af0f98fa7cf9bc2d3c30478a2191ed40b4ab194e35948dc","source":{"kind":"arxiv","id":"1902.03097","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.03097","created_at":"2026-05-17T23:54:27Z"},{"alias_kind":"arxiv_version","alias_value":"1902.03097v1","created_at":"2026-05-17T23:54:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.03097","created_at":"2026-05-17T23:54:27Z"},{"alias_kind":"pith_short_12","alias_value":"WSZVQKQ7JY4J","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"WSZVQKQ7JY4JC2XQ","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"WSZVQKQ7","created_at":"2026-05-18T12:33:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:WSZVQKQ7JY4JC2XQ7GH2PT43YL","target":"record","payload":{"canonical_record":{"source":{"id":"1902.03097","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2019-01-29T11:57:53Z","cross_cats_sorted":["cs.LG","stat.AP","stat.ML"],"title_canon_sha256":"b0f43e064722e5f6bcaf3849fa950b83f830a7447ffe5846c1904d6e1ee2e71a","abstract_canon_sha256":"704924e679976843d45c35d57bdfe3362621e437328b2a7341a95482866e5c61"},"schema_version":"1.0"},"canonical_sha256":"b4b3582a1f4e38916af0f98fa7cf9bc2d3c30478a2191ed40b4ab194e35948dc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:54:27.981157Z","signature_b64":"VrUBUzBYC2mc9HHQMBgxzpms9qfSXBVc5sb/LiRMArPAtuH7c/t5m10GbzPzUuTflTP34h294oe86zCe23ePBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b4b3582a1f4e38916af0f98fa7cf9bc2d3c30478a2191ed40b4ab194e35948dc","last_reissued_at":"2026-05-17T23:54:27.980659Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:54:27.980659Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.03097","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:54:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Gcgulu1eusAAKIo5T5yUebwERm2OEbaVMF6AoYadoQs5xHMC3mEbkuqm7C5BoEOrvpRZvMAjbOZO5/tuLhO0Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T03:18:18.305888Z"},"content_sha256":"2f30b533da660dff1773b636ba51d6bc7c6531f0426cd5964ed67511e59c8dc2","schema_version":"1.0","event_id":"sha256:2f30b533da660dff1773b636ba51d6bc7c6531f0426cd5964ed67511e59c8dc2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:WSZVQKQ7JY4JC2XQ7GH2PT43YL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A semi-supervised approach to message stance classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.AP","stat.ML"],"primary_cat":"cs.SI","authors_text":"Georgios Giasemidis, Ioannis Agrafiotis, Jason R. C. Nurse, Nikolaos Kaplis","submitted_at":"2019-01-29T11:57:53Z","abstract_excerpt":"Social media communications are becoming increasingly prevalent; some useful, some false, whether unwittingly or maliciously. An increasing number of rumours daily flood the social networks. Determining their veracity in an autonomous way is a very active and challenging field of research, with a variety of methods proposed. However, most of the models rely on determining the constituent messages' stance towards the rumour, a feature known as the \"wisdom of the crowd\". Although several supervised machine-learning approaches have been proposed to tackle the message stance classification problem"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.03097","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:54:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2HxU/IAdMxBGqSLavG85MNf+UEf3yF5g7h32Lo+VNift5UhyH+gaOYlQooJTVt+yv2Xyod/Bv8upaAl4ZWzsAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T03:18:18.306470Z"},"content_sha256":"8f06d3aba6db14d867c934f13eff068f5daae0892ecde88c1ddcdb731555f7a0","schema_version":"1.0","event_id":"sha256:8f06d3aba6db14d867c934f13eff068f5daae0892ecde88c1ddcdb731555f7a0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WSZVQKQ7JY4JC2XQ7GH2PT43YL/bundle.json","state_url":"https://pith.science/pith/WSZVQKQ7JY4JC2XQ7GH2PT43YL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WSZVQKQ7JY4JC2XQ7GH2PT43YL/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":"2026-05-26T03:18:18Z","links":{"resolver":"https://pith.science/pith/WSZVQKQ7JY4JC2XQ7GH2PT43YL","bundle":"https://pith.science/pith/WSZVQKQ7JY4JC2XQ7GH2PT43YL/bundle.json","state":"https://pith.science/pith/WSZVQKQ7JY4JC2XQ7GH2PT43YL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WSZVQKQ7JY4JC2XQ7GH2PT43YL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:WSZVQKQ7JY4JC2XQ7GH2PT43YL","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":"704924e679976843d45c35d57bdfe3362621e437328b2a7341a95482866e5c61","cross_cats_sorted":["cs.LG","stat.AP","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2019-01-29T11:57:53Z","title_canon_sha256":"b0f43e064722e5f6bcaf3849fa950b83f830a7447ffe5846c1904d6e1ee2e71a"},"schema_version":"1.0","source":{"id":"1902.03097","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.03097","created_at":"2026-05-17T23:54:27Z"},{"alias_kind":"arxiv_version","alias_value":"1902.03097v1","created_at":"2026-05-17T23:54:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.03097","created_at":"2026-05-17T23:54:27Z"},{"alias_kind":"pith_short_12","alias_value":"WSZVQKQ7JY4J","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"WSZVQKQ7JY4JC2XQ","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"WSZVQKQ7","created_at":"2026-05-18T12:33:30Z"}],"graph_snapshots":[{"event_id":"sha256:8f06d3aba6db14d867c934f13eff068f5daae0892ecde88c1ddcdb731555f7a0","target":"graph","created_at":"2026-05-17T23:54:27Z","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":"Social media communications are becoming increasingly prevalent; some useful, some false, whether unwittingly or maliciously. An increasing number of rumours daily flood the social networks. Determining their veracity in an autonomous way is a very active and challenging field of research, with a variety of methods proposed. However, most of the models rely on determining the constituent messages' stance towards the rumour, a feature known as the \"wisdom of the crowd\". Although several supervised machine-learning approaches have been proposed to tackle the message stance classification problem","authors_text":"Georgios Giasemidis, Ioannis Agrafiotis, Jason R. C. Nurse, Nikolaos Kaplis","cross_cats":["cs.LG","stat.AP","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2019-01-29T11:57:53Z","title":"A semi-supervised approach to message stance classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.03097","kind":"arxiv","version":1},"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":"sha256:2f30b533da660dff1773b636ba51d6bc7c6531f0426cd5964ed67511e59c8dc2","target":"record","created_at":"2026-05-17T23:54:27Z","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":"704924e679976843d45c35d57bdfe3362621e437328b2a7341a95482866e5c61","cross_cats_sorted":["cs.LG","stat.AP","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2019-01-29T11:57:53Z","title_canon_sha256":"b0f43e064722e5f6bcaf3849fa950b83f830a7447ffe5846c1904d6e1ee2e71a"},"schema_version":"1.0","source":{"id":"1902.03097","kind":"arxiv","version":1}},"canonical_sha256":"b4b3582a1f4e38916af0f98fa7cf9bc2d3c30478a2191ed40b4ab194e35948dc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b4b3582a1f4e38916af0f98fa7cf9bc2d3c30478a2191ed40b4ab194e35948dc","first_computed_at":"2026-05-17T23:54:27.980659Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:54:27.980659Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VrUBUzBYC2mc9HHQMBgxzpms9qfSXBVc5sb/LiRMArPAtuH7c/t5m10GbzPzUuTflTP34h294oe86zCe23ePBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:54:27.981157Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.03097","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2f30b533da660dff1773b636ba51d6bc7c6531f0426cd5964ed67511e59c8dc2","sha256:8f06d3aba6db14d867c934f13eff068f5daae0892ecde88c1ddcdb731555f7a0"],"state_sha256":"0d4fa44552efbabab90522f44f1d2a0da83039717570a72244e2f2254420851c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZF+mBduq22eO8gupWs7dS1dcW+FMr7ASPzOypkD1bpRE0r/sZZevhEB4x+6vLsFlkov5c36u6FDvvIrdLy5LCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T03:18:18.310066Z","bundle_sha256":"5511fd908a98301e233e3eb1db5890568156c72b464efda81c133d54a0fb6d00"}}