{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:BWBEGLEGXQXW7CLCIP7MX7GS3L","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":"387412934be65525e023ca33b114805d873aee77dc2618ab29c1551074329b3f","cross_cats_sorted":["cs.LG","cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-02-19T19:22:54Z","title_canon_sha256":"edb5330f16dfecdbe3b52b3d213412d19e5e7e9ab8823763ebbd34b523003521"},"schema_version":"1.0","source":{"id":"1902.07243","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.07243","created_at":"2026-07-05T00:21:22Z"},{"alias_kind":"arxiv_version","alias_value":"1902.07243v2","created_at":"2026-07-05T00:21:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.07243","created_at":"2026-07-05T00:21:22Z"},{"alias_kind":"pith_short_12","alias_value":"BWBEGLEGXQXW","created_at":"2026-07-05T00:21:22Z"},{"alias_kind":"pith_short_16","alias_value":"BWBEGLEGXQXW7CLC","created_at":"2026-07-05T00:21:22Z"},{"alias_kind":"pith_short_8","alias_value":"BWBEGLEG","created_at":"2026-07-05T00:21:22Z"}],"graph_snapshots":[{"event_id":"sha256:d26530fd940bddf4f4328ac0eef3aff41c451e7af8402f75931007257f47ca44","target":"graph","created_at":"2026-07-05T00:21:22Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1902.07243/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, Graph Neural Networks (GNNs), which can naturally integrate node information and topological structure, have been demonstrated to be powerful in learning on graph data. These advantages of GNNs provide great potential to advance social recommendation since data in social recommender systems can be represented as user-user social graph and user-item graph; and learning latent factors of users and items is the key. However, building social recommender systems based on GNNs faces challenges. For example, the user-item graph encodes both interactions and their associated opinions;","authors_text":"Dawei Yin, Eric Zhao, Jiliang Tang, Qing Li, Wenqi Fan, Yao Ma, Yuan He","cross_cats":["cs.LG","cs.SI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-02-19T19:22:54Z","title":"Graph Neural Networks for Social Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.07243","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:ae214d5486a7fd825ec07d6e71a0455261a726081c642bc8e1406aacf3fce140","target":"record","created_at":"2026-07-05T00:21:22Z","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":"387412934be65525e023ca33b114805d873aee77dc2618ab29c1551074329b3f","cross_cats_sorted":["cs.LG","cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-02-19T19:22:54Z","title_canon_sha256":"edb5330f16dfecdbe3b52b3d213412d19e5e7e9ab8823763ebbd34b523003521"},"schema_version":"1.0","source":{"id":"1902.07243","kind":"arxiv","version":2}},"canonical_sha256":"0d82432c86bc2f6f896243fecbfcd2daf40a4c81b578cba79d6e40274a7a3069","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0d82432c86bc2f6f896243fecbfcd2daf40a4c81b578cba79d6e40274a7a3069","first_computed_at":"2026-07-05T00:21:22.666686Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:21:22.666686Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XMyxXKtBgNgQFWrEkOAR2MyJ1xjmsStjTAC8N6E2ts/C9bd3Emam87JEY9rAmx0s2sNUibC0D4R4wk7j3ROaBw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:21:22.667168Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.07243","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ae214d5486a7fd825ec07d6e71a0455261a726081c642bc8e1406aacf3fce140","sha256:d26530fd940bddf4f4328ac0eef3aff41c451e7af8402f75931007257f47ca44"],"state_sha256":"75ef277e50fa3a0622fe52cbca25401d418bd96dc516fc79c4e9fbf3a1891948"}