{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:QNGHVQ6SNK2YYY4ZZGACPYEKEZ","short_pith_number":"pith:QNGHVQ6S","canonical_record":{"source":{"id":"2307.13106","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-07-24T19:54:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"be06cbd8f6ebf3daee5e5270abcde8a724f31ae9fddc83038e0420d71078a5b8","abstract_canon_sha256":"68862262f175078063ea2b729a5ab9efd18439721e43eb638147322a19442fec"},"schema_version":"1.0"},"canonical_sha256":"834c7ac3d26ab58c6399c98027e08a266afaee211ef5c85d75311f8f946bcfcd","source":{"kind":"arxiv","id":"2307.13106","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.13106","created_at":"2026-07-05T06:34:09Z"},{"alias_kind":"arxiv_version","alias_value":"2307.13106v1","created_at":"2026-07-05T06:34:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.13106","created_at":"2026-07-05T06:34:09Z"},{"alias_kind":"pith_short_12","alias_value":"QNGHVQ6SNK2Y","created_at":"2026-07-05T06:34:09Z"},{"alias_kind":"pith_short_16","alias_value":"QNGHVQ6SNK2YYY4Z","created_at":"2026-07-05T06:34:09Z"},{"alias_kind":"pith_short_8","alias_value":"QNGHVQ6S","created_at":"2026-07-05T06:34:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:QNGHVQ6SNK2YYY4ZZGACPYEKEZ","target":"record","payload":{"canonical_record":{"source":{"id":"2307.13106","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-07-24T19:54:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"be06cbd8f6ebf3daee5e5270abcde8a724f31ae9fddc83038e0420d71078a5b8","abstract_canon_sha256":"68862262f175078063ea2b729a5ab9efd18439721e43eb638147322a19442fec"},"schema_version":"1.0"},"canonical_sha256":"834c7ac3d26ab58c6399c98027e08a266afaee211ef5c85d75311f8f946bcfcd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:34:09.106140Z","signature_b64":"EQQ50zzk+9LH/8bjm89tLSMNzxrc3dUPDA9z8H4oek+z1jQ69/wp5LpyC+anc1e+btgy7G+AdHQkmCtpL9imAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"834c7ac3d26ab58c6399c98027e08a266afaee211ef5c85d75311f8f946bcfcd","last_reissued_at":"2026-07-05T06:34:09.105689Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:34:09.105689Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2307.13106","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":"2026-07-05T06:34:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VAS110m0aC8U3cRFsNio3/Ibpc7lvNNOcCcZLGIAbuiKCPWFEwlU7sJ/lgZAKjE0CsEGd91MYQiQbKkupgg6BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T03:29:42.693790Z"},"content_sha256":"9432b29d7e668cfc6b3f3cfa5d4ed8816e9549f8cd25daa84749b98bc627454e","schema_version":"1.0","event_id":"sha256:9432b29d7e668cfc6b3f3cfa5d4ed8816e9549f8cd25daa84749b98bc627454e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:QNGHVQ6SNK2YYY4ZZGACPYEKEZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"How to use LLMs for Text Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Petter T\\\"ornberg","submitted_at":"2023-07-24T19:54:15Z","abstract_excerpt":"This guide introduces Large Language Models (LLM) as a highly versatile text analysis method within the social sciences. As LLMs are easy-to-use, cheap, fast, and applicable on a broad range of text analysis tasks, ranging from text annotation and classification to sentiment analysis and critical discourse analysis, many scholars believe that LLMs will transform how we do text analysis. This how-to guide is aimed at students and researchers with limited programming experience, and offers a simple introduction to how LLMs can be used for text analysis in your own research project, as well as ad"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.13106","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/2307.13106/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":"2026-07-05T06:34:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SSq72n4AxE+JVm9wd9i/fOaZWGcXjUD4vp6RTpvEG/0mjWNFrVk2pZ5wlyTIJrKyZJGU5J6WL8DyFUgZuGMfDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T03:29:42.694459Z"},"content_sha256":"376fc2c706cc4d59f01a8a9e8edaf1fd9ee93f909f72cfe29615b1a746e12ccf","schema_version":"1.0","event_id":"sha256:376fc2c706cc4d59f01a8a9e8edaf1fd9ee93f909f72cfe29615b1a746e12ccf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QNGHVQ6SNK2YYY4ZZGACPYEKEZ/bundle.json","state_url":"https://pith.science/pith/QNGHVQ6SNK2YYY4ZZGACPYEKEZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QNGHVQ6SNK2YYY4ZZGACPYEKEZ/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":"2026-08-13T03:29:42Z","links":{"resolver":"https://pith.science/pith/QNGHVQ6SNK2YYY4ZZGACPYEKEZ","bundle":"https://pith.science/pith/QNGHVQ6SNK2YYY4ZZGACPYEKEZ/bundle.json","state":"https://pith.science/pith/QNGHVQ6SNK2YYY4ZZGACPYEKEZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QNGHVQ6SNK2YYY4ZZGACPYEKEZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:QNGHVQ6SNK2YYY4ZZGACPYEKEZ","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":"68862262f175078063ea2b729a5ab9efd18439721e43eb638147322a19442fec","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-07-24T19:54:15Z","title_canon_sha256":"be06cbd8f6ebf3daee5e5270abcde8a724f31ae9fddc83038e0420d71078a5b8"},"schema_version":"1.0","source":{"id":"2307.13106","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.13106","created_at":"2026-07-05T06:34:09Z"},{"alias_kind":"arxiv_version","alias_value":"2307.13106v1","created_at":"2026-07-05T06:34:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.13106","created_at":"2026-07-05T06:34:09Z"},{"alias_kind":"pith_short_12","alias_value":"QNGHVQ6SNK2Y","created_at":"2026-07-05T06:34:09Z"},{"alias_kind":"pith_short_16","alias_value":"QNGHVQ6SNK2YYY4Z","created_at":"2026-07-05T06:34:09Z"},{"alias_kind":"pith_short_8","alias_value":"QNGHVQ6S","created_at":"2026-07-05T06:34:09Z"}],"graph_snapshots":[{"event_id":"sha256:376fc2c706cc4d59f01a8a9e8edaf1fd9ee93f909f72cfe29615b1a746e12ccf","target":"graph","created_at":"2026-07-05T06:34:09Z","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/2307.13106/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This guide introduces Large Language Models (LLM) as a highly versatile text analysis method within the social sciences. As LLMs are easy-to-use, cheap, fast, and applicable on a broad range of text analysis tasks, ranging from text annotation and classification to sentiment analysis and critical discourse analysis, many scholars believe that LLMs will transform how we do text analysis. This how-to guide is aimed at students and researchers with limited programming experience, and offers a simple introduction to how LLMs can be used for text analysis in your own research project, as well as ad","authors_text":"Petter T\\\"ornberg","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-07-24T19:54:15Z","title":"How to use LLMs for Text Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.13106","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":"sha256:9432b29d7e668cfc6b3f3cfa5d4ed8816e9549f8cd25daa84749b98bc627454e","target":"record","created_at":"2026-07-05T06:34:09Z","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":"68862262f175078063ea2b729a5ab9efd18439721e43eb638147322a19442fec","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-07-24T19:54:15Z","title_canon_sha256":"be06cbd8f6ebf3daee5e5270abcde8a724f31ae9fddc83038e0420d71078a5b8"},"schema_version":"1.0","source":{"id":"2307.13106","kind":"arxiv","version":1}},"canonical_sha256":"834c7ac3d26ab58c6399c98027e08a266afaee211ef5c85d75311f8f946bcfcd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"834c7ac3d26ab58c6399c98027e08a266afaee211ef5c85d75311f8f946bcfcd","first_computed_at":"2026-07-05T06:34:09.105689Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:34:09.105689Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EQQ50zzk+9LH/8bjm89tLSMNzxrc3dUPDA9z8H4oek+z1jQ69/wp5LpyC+anc1e+btgy7G+AdHQkmCtpL9imAA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:34:09.106140Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.13106","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9432b29d7e668cfc6b3f3cfa5d4ed8816e9549f8cd25daa84749b98bc627454e","sha256:376fc2c706cc4d59f01a8a9e8edaf1fd9ee93f909f72cfe29615b1a746e12ccf"],"state_sha256":"9754970f83192975067680aa9f16d17669fcba33eef1bcfbdd9a98c2505b6859"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2sAoR90QrUpKzh7t+6/DYwdMn8TKFpxGFMR1vOeY+XBAy9DAgT4J5js/btx2v1IpJREVF3penHJIQvnsSfxUBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T03:29:42.697592Z","bundle_sha256":"ad391fc3e3f14c0e6a5278f8436c282a9c64315ddd17eb8868bf2156a19e29a8"}}