{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:YMQ6X7NGXQZJCG6WS4JBDSYZJ4","short_pith_number":"pith:YMQ6X7NG","canonical_record":{"source":{"id":"2510.26172","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2025-10-30T06:22:49Z","cross_cats_sorted":["cs.AI","cs.SI"],"title_canon_sha256":"14b56dd9d99f9c7be688bd21889a0017143e220ae5e7b7cb21030b042741f299","abstract_canon_sha256":"0a701424c513bddd9735d05451b1a81431c436bfe6e40326435e1363dfd61a23"},"schema_version":"1.0"},"canonical_sha256":"c321ebfda6bc32911bd6971211cb194f2523cc4611cd9314ee478656f7af1b7c","source":{"kind":"arxiv","id":"2510.26172","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.26172","created_at":"2026-07-31T01:32:44Z"},{"alias_kind":"arxiv_version","alias_value":"2510.26172v2","created_at":"2026-07-31T01:32:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.26172","created_at":"2026-07-31T01:32:44Z"},{"alias_kind":"pith_short_12","alias_value":"YMQ6X7NGXQZJ","created_at":"2026-07-31T01:32:44Z"},{"alias_kind":"pith_short_16","alias_value":"YMQ6X7NGXQZJCG6W","created_at":"2026-07-31T01:32:44Z"},{"alias_kind":"pith_short_8","alias_value":"YMQ6X7NG","created_at":"2026-07-31T01:32:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:YMQ6X7NGXQZJCG6WS4JBDSYZJ4","target":"record","payload":{"canonical_record":{"source":{"id":"2510.26172","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2025-10-30T06:22:49Z","cross_cats_sorted":["cs.AI","cs.SI"],"title_canon_sha256":"14b56dd9d99f9c7be688bd21889a0017143e220ae5e7b7cb21030b042741f299","abstract_canon_sha256":"0a701424c513bddd9735d05451b1a81431c436bfe6e40326435e1363dfd61a23"},"schema_version":"1.0"},"canonical_sha256":"c321ebfda6bc32911bd6971211cb194f2523cc4611cd9314ee478656f7af1b7c","receipt":{"kind":"pith_receipt","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c321ebfda6bc32911bd6971211cb194f2523cc4611cd9314ee478656f7af1b7c","last_reissued_at":"2026-07-31T01:32:44.082074Z","signature_status":"unsigned_v0","first_computed_at":"2026-07-31T01:32:44.082074Z"},"source_kind":"arxiv","source_id":"2510.26172","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":"2026-07-31T01:32:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7YSxJmjJ2MnUZlsFGyGJX6ST+s51HvvUa7DVCIs9JsVuixeempSDdQuhSNj8yesxRla7LtKfHMN4EtUy1zk8Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T05:03:24.889085Z"},"content_sha256":"2f9b6c1765eb0972620101c1d13844a65aa262a70f407129d04d2bbe6f5b9ca5","schema_version":"1.0","event_id":"sha256:2f9b6c1765eb0972620101c1d13844a65aa262a70f407129d04d2bbe6f5b9ca5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:YMQ6X7NGXQZJCG6WS4JBDSYZJ4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Linking Heterogeneous Data with Coordinated Agent Flows for Social Media Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.SI"],"primary_cat":"cs.HC","authors_text":"Dazhen Deng, Linyu Qin, Shifu Chen, Sijia Xu, Tai-Quan Peng, Yingcai Wu, Zhihong Xu","submitted_at":"2025-10-30T06:22:49Z","abstract_excerpt":"Social media platforms generate volumes of heterogeneous data, capturing user behaviors, textual content, and network structures. Analyzing such data is crucial for understanding phenomena such as opinion dynamics, community formation, and information diffusion. However, discovering insights from this complex landscape is exploratory, conceptually challenging, and requires expertise in social media mining and visualization. Existing automated approaches, including large language models (LLMs), remain largely confined to structured tabular data and cannot adequately address the heterogeneity of"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.26172","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2510.26172/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-31T01:32:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WdRRw2CQZM2Ze34/qyKma1Kofarh0IPcJt/cmHX6jY/g3pw1tlumgXirHN6HKr4qGwSALeWaqB7ZGfFJm+XsBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T05:03:24.889675Z"},"content_sha256":"aeaccc591c0a1c7e82690287be4b7ce560231303059e30399db42ae2c369b93d","schema_version":"1.0","event_id":"sha256:aeaccc591c0a1c7e82690287be4b7ce560231303059e30399db42ae2c369b93d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YMQ6X7NGXQZJCG6WS4JBDSYZJ4/bundle.json","state_url":"https://pith.science/pith/YMQ6X7NGXQZJCG6WS4JBDSYZJ4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YMQ6X7NGXQZJCG6WS4JBDSYZJ4/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":"2026-08-05T05:03:24Z","links":{"resolver":"https://pith.science/pith/YMQ6X7NGXQZJCG6WS4JBDSYZJ4","bundle":"https://pith.science/pith/YMQ6X7NGXQZJCG6WS4JBDSYZJ4/bundle.json","state":"https://pith.science/pith/YMQ6X7NGXQZJCG6WS4JBDSYZJ4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YMQ6X7NGXQZJCG6WS4JBDSYZJ4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:YMQ6X7NGXQZJCG6WS4JBDSYZJ4","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":"0a701424c513bddd9735d05451b1a81431c436bfe6e40326435e1363dfd61a23","cross_cats_sorted":["cs.AI","cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2025-10-30T06:22:49Z","title_canon_sha256":"14b56dd9d99f9c7be688bd21889a0017143e220ae5e7b7cb21030b042741f299"},"schema_version":"1.0","source":{"id":"2510.26172","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.26172","created_at":"2026-07-31T01:32:44Z"},{"alias_kind":"arxiv_version","alias_value":"2510.26172v2","created_at":"2026-07-31T01:32:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.26172","created_at":"2026-07-31T01:32:44Z"},{"alias_kind":"pith_short_12","alias_value":"YMQ6X7NGXQZJ","created_at":"2026-07-31T01:32:44Z"},{"alias_kind":"pith_short_16","alias_value":"YMQ6X7NGXQZJCG6W","created_at":"2026-07-31T01:32:44Z"},{"alias_kind":"pith_short_8","alias_value":"YMQ6X7NG","created_at":"2026-07-31T01:32:44Z"}],"graph_snapshots":[{"event_id":"sha256:aeaccc591c0a1c7e82690287be4b7ce560231303059e30399db42ae2c369b93d","target":"graph","created_at":"2026-07-31T01:32:44Z","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/2510.26172/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Social media platforms generate volumes of heterogeneous data, capturing user behaviors, textual content, and network structures. Analyzing such data is crucial for understanding phenomena such as opinion dynamics, community formation, and information diffusion. However, discovering insights from this complex landscape is exploratory, conceptually challenging, and requires expertise in social media mining and visualization. Existing automated approaches, including large language models (LLMs), remain largely confined to structured tabular data and cannot adequately address the heterogeneity of","authors_text":"Dazhen Deng, Linyu Qin, Shifu Chen, Sijia Xu, Tai-Quan Peng, Yingcai Wu, Zhihong Xu","cross_cats":["cs.AI","cs.SI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2025-10-30T06:22:49Z","title":"Linking Heterogeneous Data with Coordinated Agent Flows for Social Media Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.26172","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":"sha256:2f9b6c1765eb0972620101c1d13844a65aa262a70f407129d04d2bbe6f5b9ca5","target":"record","created_at":"2026-07-31T01:32:44Z","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":"0a701424c513bddd9735d05451b1a81431c436bfe6e40326435e1363dfd61a23","cross_cats_sorted":["cs.AI","cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2025-10-30T06:22:49Z","title_canon_sha256":"14b56dd9d99f9c7be688bd21889a0017143e220ae5e7b7cb21030b042741f299"},"schema_version":"1.0","source":{"id":"2510.26172","kind":"arxiv","version":2}},"canonical_sha256":"c321ebfda6bc32911bd6971211cb194f2523cc4611cd9314ee478656f7af1b7c","receipt":{"builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c321ebfda6bc32911bd6971211cb194f2523cc4611cd9314ee478656f7af1b7c","first_computed_at":"2026-07-31T01:32:44.082074Z","kind":"pith_receipt","last_reissued_at":"2026-07-31T01:32:44.082074Z","receipt_version":"0.3","signature_status":"unsigned_v0"},"source_id":"2510.26172","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2f9b6c1765eb0972620101c1d13844a65aa262a70f407129d04d2bbe6f5b9ca5","sha256:aeaccc591c0a1c7e82690287be4b7ce560231303059e30399db42ae2c369b93d"],"state_sha256":"795859d5287e069da23a1557a3bbb3c41b19b423331f6c659279c51230980c79"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mKlQma8/PiTl7cN4bfRg4noVJq20KF7GN0FbimQDvochJwLEFa1FoeUolKX/j51inL66swf9oLh31SbwOAlgBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T05:03:24.893091Z","bundle_sha256":"d5930c85aeb59097286546b8268fea0c2858f5d366b8d9c3a8d38f05c49e162a"}}