{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:KWIQ4NPNRLIIDSB5A4B2QOZ2X2","short_pith_number":"pith:KWIQ4NPN","canonical_record":{"source":{"id":"1708.01677","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-08-04T22:35:50Z","cross_cats_sorted":["cs.CL","physics.data-an","physics.soc-ph"],"title_canon_sha256":"e1a20b32b2327be4c5b24b5a720d33a0461f0fa2aca5f3eda6658e2872af6139","abstract_canon_sha256":"a6b433a404d3bddffcc272a618c239036e4b85a02e9509c882931bd14b9ba447"},"schema_version":"1.0"},"canonical_sha256":"55910e35ed8ad081c83d0703a83b3abe8c52251c12ec53a4f167c8942929f952","source":{"kind":"arxiv","id":"1708.01677","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.01677","created_at":"2026-05-18T00:10:24Z"},{"alias_kind":"arxiv_version","alias_value":"1708.01677v2","created_at":"2026-05-18T00:10:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.01677","created_at":"2026-05-18T00:10:24Z"},{"alias_kind":"pith_short_12","alias_value":"KWIQ4NPNRLII","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"KWIQ4NPNRLIIDSB5","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"KWIQ4NPN","created_at":"2026-05-18T12:31:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:KWIQ4NPNRLIIDSB5A4B2QOZ2X2","target":"record","payload":{"canonical_record":{"source":{"id":"1708.01677","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-08-04T22:35:50Z","cross_cats_sorted":["cs.CL","physics.data-an","physics.soc-ph"],"title_canon_sha256":"e1a20b32b2327be4c5b24b5a720d33a0461f0fa2aca5f3eda6658e2872af6139","abstract_canon_sha256":"a6b433a404d3bddffcc272a618c239036e4b85a02e9509c882931bd14b9ba447"},"schema_version":"1.0"},"canonical_sha256":"55910e35ed8ad081c83d0703a83b3abe8c52251c12ec53a4f167c8942929f952","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:10:24.380209Z","signature_b64":"/hJlq/Byzr26A6buCmqVZAyL3BI9Hv48kn1NFlhB/2+/V6OqvE6TbXKKdvn1n3HblAJrmh1ts4ZtxeBd/vWLBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"55910e35ed8ad081c83d0703a83b3abe8c52251c12ec53a4f167c8942929f952","last_reissued_at":"2026-05-18T00:10:24.379571Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:10:24.379571Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.01677","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":"2026-05-18T00:10:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fVqhnA+rcbckGmoySH5QPBCjJjbdkTZtoig8kNk2kel9rUgIhUS77CEmjM+FGetITdyEirklMjalzcAnv5dgCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T08:16:07.726324Z"},"content_sha256":"18fa9b4ee4b1c7f7a3a2d1a90b6db7a4e1ffcb6e67083a454d236ff87c57f3cb","schema_version":"1.0","event_id":"sha256:18fa9b4ee4b1c7f7a3a2d1a90b6db7a4e1ffcb6e67083a454d236ff87c57f3cb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:KWIQ4NPNRLIIDSB5A4B2QOZ2X2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A network approach to topic models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","physics.data-an","physics.soc-ph"],"primary_cat":"stat.ML","authors_text":"Eduardo G. Altmann, Martin Gerlach, Tiago P. Peixoto","submitted_at":"2017-08-04T22:35:50Z","abstract_excerpt":"One of the main computational and scientific challenges in the modern age is to extract useful information from unstructured texts. Topic models are one popular machine-learning approach which infers the latent topical structure of a collection of documents. Despite their success --- in particular of its most widely used variant called Latent Dirichlet Allocation (LDA) --- and numerous applications in sociology, history, and linguistics, topic models are known to suffer from severe conceptual and practical problems, e.g. a lack of justification for the Bayesian priors, discrepancies with stati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.01677","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":"2026-05-18T00:10:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/IDDisftP5DlylWF6xgbgSwKd/uhP4gPhO+RH5gge8xFES0m/Dk8GeikIL0mAc7NdvROXhJLIEft5G/dO+bpDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T08:16:07.726970Z"},"content_sha256":"4aa8e1305407346193859ca0fc32a7ae0827f645a647bcb085ca0df3c9f36492","schema_version":"1.0","event_id":"sha256:4aa8e1305407346193859ca0fc32a7ae0827f645a647bcb085ca0df3c9f36492"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KWIQ4NPNRLIIDSB5A4B2QOZ2X2/bundle.json","state_url":"https://pith.science/pith/KWIQ4NPNRLIIDSB5A4B2QOZ2X2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KWIQ4NPNRLIIDSB5A4B2QOZ2X2/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":"2026-05-23T08:16:07Z","links":{"resolver":"https://pith.science/pith/KWIQ4NPNRLIIDSB5A4B2QOZ2X2","bundle":"https://pith.science/pith/KWIQ4NPNRLIIDSB5A4B2QOZ2X2/bundle.json","state":"https://pith.science/pith/KWIQ4NPNRLIIDSB5A4B2QOZ2X2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KWIQ4NPNRLIIDSB5A4B2QOZ2X2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:KWIQ4NPNRLIIDSB5A4B2QOZ2X2","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":"a6b433a404d3bddffcc272a618c239036e4b85a02e9509c882931bd14b9ba447","cross_cats_sorted":["cs.CL","physics.data-an","physics.soc-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-08-04T22:35:50Z","title_canon_sha256":"e1a20b32b2327be4c5b24b5a720d33a0461f0fa2aca5f3eda6658e2872af6139"},"schema_version":"1.0","source":{"id":"1708.01677","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.01677","created_at":"2026-05-18T00:10:24Z"},{"alias_kind":"arxiv_version","alias_value":"1708.01677v2","created_at":"2026-05-18T00:10:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.01677","created_at":"2026-05-18T00:10:24Z"},{"alias_kind":"pith_short_12","alias_value":"KWIQ4NPNRLII","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"KWIQ4NPNRLIIDSB5","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"KWIQ4NPN","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:4aa8e1305407346193859ca0fc32a7ae0827f645a647bcb085ca0df3c9f36492","target":"graph","created_at":"2026-05-18T00:10:24Z","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":"One of the main computational and scientific challenges in the modern age is to extract useful information from unstructured texts. Topic models are one popular machine-learning approach which infers the latent topical structure of a collection of documents. Despite their success --- in particular of its most widely used variant called Latent Dirichlet Allocation (LDA) --- and numerous applications in sociology, history, and linguistics, topic models are known to suffer from severe conceptual and practical problems, e.g. a lack of justification for the Bayesian priors, discrepancies with stati","authors_text":"Eduardo G. Altmann, Martin Gerlach, Tiago P. Peixoto","cross_cats":["cs.CL","physics.data-an","physics.soc-ph"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-08-04T22:35:50Z","title":"A network approach to topic models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.01677","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":"sha256:18fa9b4ee4b1c7f7a3a2d1a90b6db7a4e1ffcb6e67083a454d236ff87c57f3cb","target":"record","created_at":"2026-05-18T00:10:24Z","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":"a6b433a404d3bddffcc272a618c239036e4b85a02e9509c882931bd14b9ba447","cross_cats_sorted":["cs.CL","physics.data-an","physics.soc-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-08-04T22:35:50Z","title_canon_sha256":"e1a20b32b2327be4c5b24b5a720d33a0461f0fa2aca5f3eda6658e2872af6139"},"schema_version":"1.0","source":{"id":"1708.01677","kind":"arxiv","version":2}},"canonical_sha256":"55910e35ed8ad081c83d0703a83b3abe8c52251c12ec53a4f167c8942929f952","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"55910e35ed8ad081c83d0703a83b3abe8c52251c12ec53a4f167c8942929f952","first_computed_at":"2026-05-18T00:10:24.379571Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:10:24.379571Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/hJlq/Byzr26A6buCmqVZAyL3BI9Hv48kn1NFlhB/2+/V6OqvE6TbXKKdvn1n3HblAJrmh1ts4ZtxeBd/vWLBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:10:24.380209Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.01677","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:18fa9b4ee4b1c7f7a3a2d1a90b6db7a4e1ffcb6e67083a454d236ff87c57f3cb","sha256:4aa8e1305407346193859ca0fc32a7ae0827f645a647bcb085ca0df3c9f36492"],"state_sha256":"1c8c67026f48e48e0ea87bc7e45fcbb72fe877d03ca8121332c4a08a1586c6e5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c5aLPAenoK05q1ADs2geu5ivYSNurZeSxkz+A8MBYk/j48m4XtFDmMrZeEzLFFSFq6cjfai0yAB1kEeTh9YvAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T08:16:07.730339Z","bundle_sha256":"c62147da61a8bcf2ea739829b74d0158017fb593e5d52bcfab7db533af574374"}}