{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:GZVSHXNWYIIQAPSF3ZIROTBGH7","short_pith_number":"pith:GZVSHXNW","canonical_record":{"source":{"id":"2604.01690","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2026-04-02T06:46:43Z","cross_cats_sorted":[],"title_canon_sha256":"534ada1f96c2434a97c50812800996bddcb46f71c896860c97b33ccfea52c83a","abstract_canon_sha256":"a1f883d52770dfeb84b8ab1856dab16b5461e0b5e60b7d1bfecad0e174000108"},"schema_version":"1.0"},"canonical_sha256":"366b23ddb6c211003e45de51174c263ff27eb7ee4ec5c5b5cfb90c9c504a45f0","source":{"kind":"arxiv","id":"2604.01690","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.01690","created_at":"2026-05-18T03:09:22Z"},{"alias_kind":"arxiv_version","alias_value":"2604.01690v2","created_at":"2026-05-18T03:09:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.01690","created_at":"2026-05-18T03:09:22Z"},{"alias_kind":"pith_short_12","alias_value":"GZVSHXNWYIIQ","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"GZVSHXNWYIIQAPSF","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"GZVSHXNW","created_at":"2026-05-18T12:33:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:GZVSHXNWYIIQAPSF3ZIROTBGH7","target":"record","payload":{"canonical_record":{"source":{"id":"2604.01690","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2026-04-02T06:46:43Z","cross_cats_sorted":[],"title_canon_sha256":"534ada1f96c2434a97c50812800996bddcb46f71c896860c97b33ccfea52c83a","abstract_canon_sha256":"a1f883d52770dfeb84b8ab1856dab16b5461e0b5e60b7d1bfecad0e174000108"},"schema_version":"1.0"},"canonical_sha256":"366b23ddb6c211003e45de51174c263ff27eb7ee4ec5c5b5cfb90c9c504a45f0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:09:22.433001Z","signature_b64":"mc88M8ka/ddKbEkXuXn0FybD6rvz2hYkKNXwhzTOKyTwSsmMeen4CgedE559QAVFiegCSM/HY5jDcBXdPwRWBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"366b23ddb6c211003e45de51174c263ff27eb7ee4ec5c5b5cfb90c9c504a45f0","last_reissued_at":"2026-05-18T03:09:22.432188Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:09:22.432188Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2604.01690","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":"2026-05-18T03:09:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/SXzpoCYLtdvlQxctraCJUA4XR6K3ceezpgoAdHxgfHaWB3hv87bnpmixXaXdXl6iKVMNUeHhpC+PC9Lr57vCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T15:45:06.834186Z"},"content_sha256":"b70c67c97836c6ff28522f3d0618971e1007c80009f74366eed9033de82123b9","schema_version":"1.0","event_id":"sha256:b70c67c97836c6ff28522f3d0618971e1007c80009f74366eed9033de82123b9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:GZVSHXNWYIIQAPSF3ZIROTBGH7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scale over Preference: The Impact of AI-Generated Content on Online Content Ecology","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"AI-generated content creators achieve aggregate engagement comparable to human creators through high-volume production despite user preference for human content.","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Chenyi Lei, Fengbin Zhu, Fuli Feng, Han Li, Tianhao Shi, Tian Yang, Wenwu Ou, Xiaoyan Zhao, Yang Song, Yang Zhang, Yongdong Zhang","submitted_at":"2026-04-02T06:46:43Z","abstract_excerpt":"The rapid proliferation of Artificial Intelligence-Generated Content (AIGC) is fundamentally restructuring online content ecologies, necessitating a rigorous examination of its behavioral and distributional implications. Leveraging a comprehensive longitudinal dataset comprising tens of millions of users from a leading Chinese video-sharing platform, this study elucidated the distinct creation and consumption behaviors characterizing AIGC versus Human-Generated Content (HGC). We identified a prevalent scale-over-preference dynamic, wherein AIGC creators achieve aggregate engagement comparable "},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"A prevalent scale-over-preference dynamic, wherein AIGC creators achieve aggregate engagement comparable to HGC creators through high-volume production, despite a marked consumer preference for HGC.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the observed behaviors and preferences are generalizable beyond the specific platform and dataset, and that the algorithmic moderation is accurately identified without confounding factors.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"AIGC creators match HGC engagement via high-volume production despite consumer preference for HGC, with algorithms moderating the effect.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"AI-generated content creators achieve aggregate engagement comparable to human creators through high-volume production despite user preference for human content.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"f2e45fba30072f73620cfbf7b0a95652301636d90c3519ac46c603e51015896d"},"source":{"id":"2604.01690","kind":"arxiv","version":2},"verdict":{"id":"969bce86-3fd5-4b28-a943-ec0014693cde","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-14T22:10:07.526600Z","strongest_claim":"A prevalent scale-over-preference dynamic, wherein AIGC creators achieve aggregate engagement comparable to HGC creators through high-volume production, despite a marked consumer preference for HGC.","one_line_summary":"AIGC creators match HGC engagement via high-volume production despite consumer preference for HGC, with algorithms moderating the effect.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the observed behaviors and preferences are generalizable beyond the specific platform and dataset, and that the algorithmic moderation is accurately identified without confounding factors.","pith_extraction_headline":"AI-generated content creators achieve aggregate engagement comparable to human creators through high-volume production despite user preference for human content."},"references":{"count":34,"sample":[{"doi":"","year":2024,"title":"Scientific Reports14(1), 10413 (2024)","work_id":"55ac03de-64c9-410a-9b71-6bcdf64f98f9","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2025,"title":"PNAS nexus4(6), 170 (2025)","work_id":"0d0b26f1-bf53-45f1-bf23-65d68b6a35d8","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2026,"title":"Scientific Reports (2026)","work_id":"9ee74c2f-787f-44de-82b3-d1095456565a","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2022,"title":"Advances in neural information processing systems35, 27730–27744 (2022)","work_id":"a5ef1ebf-e214-4ba0-8555-04f15135a60c","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2026,"title":"Nature (2026)","work_id":"ff5858dc-4402-460f-8b6d-68313579cb10","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":34,"snapshot_sha256":"8c1a4faae9e4ac9cf75aca652c04d86c65f0a1fd55332b1cf431dc8298d87408","internal_anchors":0},"formal_canon":{"evidence_count":1,"snapshot_sha256":"3315a2c4fb1abda34f799d4136faa38fc056efef1dd3f4547ba56a14473ca5f5"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":"969bce86-3fd5-4b28-a943-ec0014693cde"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:09:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9CA6rJBTCIAwijunmt8eoqUjldiQUmz4HnGInlCYq8TQo03hMTR2Z7IjKKEWnf8dCmQQfrIBpteiu4h7gwwaAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T15:45:06.835355Z"},"content_sha256":"302ea22e5c7ed03d5c0a1e5378d78e8bcaa602b4666c480e3ea8cb292520f4d6","schema_version":"1.0","event_id":"sha256:302ea22e5c7ed03d5c0a1e5378d78e8bcaa602b4666c480e3ea8cb292520f4d6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GZVSHXNWYIIQAPSF3ZIROTBGH7/bundle.json","state_url":"https://pith.science/pith/GZVSHXNWYIIQAPSF3ZIROTBGH7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GZVSHXNWYIIQAPSF3ZIROTBGH7/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":"2026-05-31T15:45:06Z","links":{"resolver":"https://pith.science/pith/GZVSHXNWYIIQAPSF3ZIROTBGH7","bundle":"https://pith.science/pith/GZVSHXNWYIIQAPSF3ZIROTBGH7/bundle.json","state":"https://pith.science/pith/GZVSHXNWYIIQAPSF3ZIROTBGH7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GZVSHXNWYIIQAPSF3ZIROTBGH7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:GZVSHXNWYIIQAPSF3ZIROTBGH7","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":"a1f883d52770dfeb84b8ab1856dab16b5461e0b5e60b7d1bfecad0e174000108","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2026-04-02T06:46:43Z","title_canon_sha256":"534ada1f96c2434a97c50812800996bddcb46f71c896860c97b33ccfea52c83a"},"schema_version":"1.0","source":{"id":"2604.01690","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.01690","created_at":"2026-05-18T03:09:22Z"},{"alias_kind":"arxiv_version","alias_value":"2604.01690v2","created_at":"2026-05-18T03:09:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.01690","created_at":"2026-05-18T03:09:22Z"},{"alias_kind":"pith_short_12","alias_value":"GZVSHXNWYIIQ","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"GZVSHXNWYIIQAPSF","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"GZVSHXNW","created_at":"2026-05-18T12:33:37Z"}],"graph_snapshots":[{"event_id":"sha256:302ea22e5c7ed03d5c0a1e5378d78e8bcaa602b4666c480e3ea8cb292520f4d6","target":"graph","created_at":"2026-05-18T03:09:22Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"A prevalent scale-over-preference dynamic, wherein AIGC creators achieve aggregate engagement comparable to HGC creators through high-volume production, despite a marked consumer preference for HGC."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That the observed behaviors and preferences are generalizable beyond the specific platform and dataset, and that the algorithmic moderation is accurately identified without confounding factors."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"AIGC creators match HGC engagement via high-volume production despite consumer preference for HGC, with algorithms moderating the effect."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"AI-generated content creators achieve aggregate engagement comparable to human creators through high-volume production despite user preference for human content."}],"snapshot_sha256":"f2e45fba30072f73620cfbf7b0a95652301636d90c3519ac46c603e51015896d"},"formal_canon":{"evidence_count":1,"snapshot_sha256":"3315a2c4fb1abda34f799d4136faa38fc056efef1dd3f4547ba56a14473ca5f5"},"paper":{"abstract_excerpt":"The rapid proliferation of Artificial Intelligence-Generated Content (AIGC) is fundamentally restructuring online content ecologies, necessitating a rigorous examination of its behavioral and distributional implications. Leveraging a comprehensive longitudinal dataset comprising tens of millions of users from a leading Chinese video-sharing platform, this study elucidated the distinct creation and consumption behaviors characterizing AIGC versus Human-Generated Content (HGC). We identified a prevalent scale-over-preference dynamic, wherein AIGC creators achieve aggregate engagement comparable ","authors_text":"Chenyi Lei, Fengbin Zhu, Fuli Feng, Han Li, Tianhao Shi, Tian Yang, Wenwu Ou, Xiaoyan Zhao, Yang Song, Yang Zhang, Yongdong Zhang","cross_cats":[],"headline":"AI-generated content creators achieve aggregate engagement comparable to human creators through high-volume production despite user preference for human content.","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2026-04-02T06:46:43Z","title":"Scale over Preference: The Impact of AI-Generated Content on Online Content Ecology"},"references":{"count":34,"internal_anchors":0,"resolved_work":34,"sample":[{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":1,"title":"Scientific Reports14(1), 10413 (2024)","work_id":"55ac03de-64c9-410a-9b71-6bcdf64f98f9","year":2024},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":2,"title":"PNAS nexus4(6), 170 (2025)","work_id":"0d0b26f1-bf53-45f1-bf23-65d68b6a35d8","year":2025},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":3,"title":"Scientific Reports (2026)","work_id":"9ee74c2f-787f-44de-82b3-d1095456565a","year":2026},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"Advances in neural information processing systems35, 27730–27744 (2022)","work_id":"a5ef1ebf-e214-4ba0-8555-04f15135a60c","year":2022},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"title":"Nature (2026)","work_id":"ff5858dc-4402-460f-8b6d-68313579cb10","year":2026}],"snapshot_sha256":"8c1a4faae9e4ac9cf75aca652c04d86c65f0a1fd55332b1cf431dc8298d87408"},"source":{"id":"2604.01690","kind":"arxiv","version":2},"verdict":{"created_at":"2026-05-14T22:10:07.526600Z","id":"969bce86-3fd5-4b28-a943-ec0014693cde","model_set":{"reader":"grok-4.3"},"one_line_summary":"AIGC creators match HGC engagement via high-volume production despite consumer preference for HGC, with algorithms moderating the effect.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"AI-generated content creators achieve aggregate engagement comparable to human creators through high-volume production despite user preference for human content.","strongest_claim":"A prevalent scale-over-preference dynamic, wherein AIGC creators achieve aggregate engagement comparable to HGC creators through high-volume production, despite a marked consumer preference for HGC.","weakest_assumption":"That the observed behaviors and preferences are generalizable beyond the specific platform and dataset, and that the algorithmic moderation is accurately identified without confounding factors."}},"verdict_id":"969bce86-3fd5-4b28-a943-ec0014693cde"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:b70c67c97836c6ff28522f3d0618971e1007c80009f74366eed9033de82123b9","target":"record","created_at":"2026-05-18T03:09:22Z","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":"a1f883d52770dfeb84b8ab1856dab16b5461e0b5e60b7d1bfecad0e174000108","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2026-04-02T06:46:43Z","title_canon_sha256":"534ada1f96c2434a97c50812800996bddcb46f71c896860c97b33ccfea52c83a"},"schema_version":"1.0","source":{"id":"2604.01690","kind":"arxiv","version":2}},"canonical_sha256":"366b23ddb6c211003e45de51174c263ff27eb7ee4ec5c5b5cfb90c9c504a45f0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"366b23ddb6c211003e45de51174c263ff27eb7ee4ec5c5b5cfb90c9c504a45f0","first_computed_at":"2026-05-18T03:09:22.432188Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:09:22.432188Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mc88M8ka/ddKbEkXuXn0FybD6rvz2hYkKNXwhzTOKyTwSsmMeen4CgedE559QAVFiegCSM/HY5jDcBXdPwRWBw==","signature_status":"signed_v1","signed_at":"2026-05-18T03:09:22.433001Z","signed_message":"canonical_sha256_bytes"},"source_id":"2604.01690","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b70c67c97836c6ff28522f3d0618971e1007c80009f74366eed9033de82123b9","sha256:302ea22e5c7ed03d5c0a1e5378d78e8bcaa602b4666c480e3ea8cb292520f4d6"],"state_sha256":"c3a3e0b33f9109d0efaff86600c00b18f2d0c7fd980d5aa8a6c7de6dcc3fb3ca"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dP+NdlduNXQE+kUIJ0aQKRbqM0fG2Jt2nFlYWjAeNCbYwE588oRWu7pDkVoWcAkAeNL8l/l3IVPgvjgLwYG0BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T15:45:06.840268Z","bundle_sha256":"8a1eca1dbd13cc1465dc5695471a1150c0e54eeb2daf0f319e3637dc225e89e0"}}