{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:45JRJADOXEHSELC2NVWYN7S2Y7","short_pith_number":"pith:45JRJADO","canonical_record":{"source":{"id":"2210.00707","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2022-10-03T04:21:08Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"426f57298b8024bfaa1159baf6e5e339da142ec60ef28ad35c33271b73c8e794","abstract_canon_sha256":"ebe18b88ced9f7b93563dbe539863b0aa4b841de16600959de985e91e8b0c1ea"},"schema_version":"1.0"},"canonical_sha256":"e75314806eb90f222c5a6d6d86fe5ac7d6157a10cc7725cfbe6ca0a02ecfce2e","source":{"kind":"arxiv","id":"2210.00707","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.00707","created_at":"2026-07-05T05:02:46Z"},{"alias_kind":"arxiv_version","alias_value":"2210.00707v1","created_at":"2026-07-05T05:02:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.00707","created_at":"2026-07-05T05:02:46Z"},{"alias_kind":"pith_short_12","alias_value":"45JRJADOXEHS","created_at":"2026-07-05T05:02:46Z"},{"alias_kind":"pith_short_16","alias_value":"45JRJADOXEHSELC2","created_at":"2026-07-05T05:02:46Z"},{"alias_kind":"pith_short_8","alias_value":"45JRJADO","created_at":"2026-07-05T05:02:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:45JRJADOXEHSELC2NVWYN7S2Y7","target":"record","payload":{"canonical_record":{"source":{"id":"2210.00707","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2022-10-03T04:21:08Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"426f57298b8024bfaa1159baf6e5e339da142ec60ef28ad35c33271b73c8e794","abstract_canon_sha256":"ebe18b88ced9f7b93563dbe539863b0aa4b841de16600959de985e91e8b0c1ea"},"schema_version":"1.0"},"canonical_sha256":"e75314806eb90f222c5a6d6d86fe5ac7d6157a10cc7725cfbe6ca0a02ecfce2e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:02:46.829054Z","signature_b64":"0ci+UnUwVnZuUeuISR7VOjfWEi3ZXFW0KdgHadgVPXWvHdxhBoztHPzke/HuWSYkCrdFFjC5CWLjl6yPZ2ECBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e75314806eb90f222c5a6d6d86fe5ac7d6157a10cc7725cfbe6ca0a02ecfce2e","last_reissued_at":"2026-07-05T05:02:46.828343Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:02:46.828343Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.00707","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":"2026-07-05T05:02:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HZ/11BcOjJ90d9vBILLFgZIIfvQ2kPlWrdH+aEs++hzZjDKVg4v/E/v8W8mRoLe1T7rmnmKleza4Ewgfu6p+BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T14:24:44.689459Z"},"content_sha256":"5a1ccbe584bfb6b18e2f12a8eef603f19db4d00f96aa8872a6f8b224c46a8a1c","schema_version":"1.0","event_id":"sha256:5a1ccbe584bfb6b18e2f12a8eef603f19db4d00f96aa8872a6f8b224c46a8a1c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:45JRJADOXEHSELC2NVWYN7S2Y7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Theme and Topic: How Qualitative Research and Topic Modeling Can Be Brought Together","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.HC","authors_text":"Dhiraj Murthy, Harry Brenton, Marco Gillies, Rapheal Olaniyan","submitted_at":"2022-10-03T04:21:08Z","abstract_excerpt":"Qualitative research is an approach to understanding social phenomenon based around human interpretation of data, particularly text. Probabilistic topic modelling is a machine learning approach that is also based around the analysis of text and often is used to in order to understand social phenomena. Both of these approaches aim to extract important themes or topics in a textual corpus and therefore we may see them as analogous to each other. However there are also considerable differences in how the two approaches function. One is a highly human interpretive process, the other is automated a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.00707","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2210.00707/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":"2026-07-05T05:02:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DJazFt8T4XLmsp3AxMiLidqwL7Y3q5vLUd8kVPUlgI69c/yGzfWZrKUnHHbtZQRQwFw7M4Z8V9fcWFleGjrLAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T14:24:44.689959Z"},"content_sha256":"bd9e93bb3135046c957b59e05d76c158c354b3c2386a221239c2adf8f173b421","schema_version":"1.0","event_id":"sha256:bd9e93bb3135046c957b59e05d76c158c354b3c2386a221239c2adf8f173b421"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/45JRJADOXEHSELC2NVWYN7S2Y7/bundle.json","state_url":"https://pith.science/pith/45JRJADOXEHSELC2NVWYN7S2Y7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/45JRJADOXEHSELC2NVWYN7S2Y7/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":"2026-08-23T14:24:44Z","links":{"resolver":"https://pith.science/pith/45JRJADOXEHSELC2NVWYN7S2Y7","bundle":"https://pith.science/pith/45JRJADOXEHSELC2NVWYN7S2Y7/bundle.json","state":"https://pith.science/pith/45JRJADOXEHSELC2NVWYN7S2Y7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/45JRJADOXEHSELC2NVWYN7S2Y7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:45JRJADOXEHSELC2NVWYN7S2Y7","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":"ebe18b88ced9f7b93563dbe539863b0aa4b841de16600959de985e91e8b0c1ea","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2022-10-03T04:21:08Z","title_canon_sha256":"426f57298b8024bfaa1159baf6e5e339da142ec60ef28ad35c33271b73c8e794"},"schema_version":"1.0","source":{"id":"2210.00707","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.00707","created_at":"2026-07-05T05:02:46Z"},{"alias_kind":"arxiv_version","alias_value":"2210.00707v1","created_at":"2026-07-05T05:02:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.00707","created_at":"2026-07-05T05:02:46Z"},{"alias_kind":"pith_short_12","alias_value":"45JRJADOXEHS","created_at":"2026-07-05T05:02:46Z"},{"alias_kind":"pith_short_16","alias_value":"45JRJADOXEHSELC2","created_at":"2026-07-05T05:02:46Z"},{"alias_kind":"pith_short_8","alias_value":"45JRJADO","created_at":"2026-07-05T05:02:46Z"}],"graph_snapshots":[{"event_id":"sha256:bd9e93bb3135046c957b59e05d76c158c354b3c2386a221239c2adf8f173b421","target":"graph","created_at":"2026-07-05T05:02:46Z","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/2210.00707/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Qualitative research is an approach to understanding social phenomenon based around human interpretation of data, particularly text. Probabilistic topic modelling is a machine learning approach that is also based around the analysis of text and often is used to in order to understand social phenomena. Both of these approaches aim to extract important themes or topics in a textual corpus and therefore we may see them as analogous to each other. However there are also considerable differences in how the two approaches function. One is a highly human interpretive process, the other is automated a","authors_text":"Dhiraj Murthy, Harry Brenton, Marco Gillies, Rapheal Olaniyan","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2022-10-03T04:21:08Z","title":"Theme and Topic: How Qualitative Research and Topic Modeling Can Be Brought Together"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.00707","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":"sha256:5a1ccbe584bfb6b18e2f12a8eef603f19db4d00f96aa8872a6f8b224c46a8a1c","target":"record","created_at":"2026-07-05T05:02:46Z","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":"ebe18b88ced9f7b93563dbe539863b0aa4b841de16600959de985e91e8b0c1ea","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2022-10-03T04:21:08Z","title_canon_sha256":"426f57298b8024bfaa1159baf6e5e339da142ec60ef28ad35c33271b73c8e794"},"schema_version":"1.0","source":{"id":"2210.00707","kind":"arxiv","version":1}},"canonical_sha256":"e75314806eb90f222c5a6d6d86fe5ac7d6157a10cc7725cfbe6ca0a02ecfce2e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e75314806eb90f222c5a6d6d86fe5ac7d6157a10cc7725cfbe6ca0a02ecfce2e","first_computed_at":"2026-07-05T05:02:46.828343Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:02:46.828343Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0ci+UnUwVnZuUeuISR7VOjfWEi3ZXFW0KdgHadgVPXWvHdxhBoztHPzke/HuWSYkCrdFFjC5CWLjl6yPZ2ECBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:02:46.829054Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.00707","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5a1ccbe584bfb6b18e2f12a8eef603f19db4d00f96aa8872a6f8b224c46a8a1c","sha256:bd9e93bb3135046c957b59e05d76c158c354b3c2386a221239c2adf8f173b421"],"state_sha256":"4fd21847bfebaf07f6f02fe8ede16cebb4ddecec82939b4bd26fa7325aabc588"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4wNWfe91HpVzVBWk2wOfpCMGvMuodvNod5mt3mVCyEUQeDiRIob10CrqkjZ3ugYQTLCSnw1+SnU7H6yEpOuwBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T14:24:44.694661Z","bundle_sha256":"829607a2e0d9c9f1d960f1876caad0e4b38f0ebab67bb35516254c6156e218c7"}}