{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:6U4JL6PGADJ222N3SUA627IBNI","short_pith_number":"pith:6U4JL6PG","canonical_record":{"source":{"id":"1703.04009","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-03-11T18:20:13Z","cross_cats_sorted":[],"title_canon_sha256":"da7ca9d740611b621077718429cd97ee38746eb014d1bb35fa7b6b176a6be2ba","abstract_canon_sha256":"91f127c29c654cf8751e3b01d08ff99f614d64c65b41ff80a3705c2418158b60"},"schema_version":"1.0"},"canonical_sha256":"f53895f9e600d3ad69bb9501ed7d016a1092709940b6e84faecee5ae1dfaf38c","source":{"kind":"arxiv","id":"1703.04009","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.04009","created_at":"2026-05-18T00:48:52Z"},{"alias_kind":"arxiv_version","alias_value":"1703.04009v1","created_at":"2026-05-18T00:48:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.04009","created_at":"2026-05-18T00:48:52Z"},{"alias_kind":"pith_short_12","alias_value":"6U4JL6PGADJ2","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_16","alias_value":"6U4JL6PGADJ222N3","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_8","alias_value":"6U4JL6PG","created_at":"2026-05-18T12:31:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:6U4JL6PGADJ222N3SUA627IBNI","target":"record","payload":{"canonical_record":{"source":{"id":"1703.04009","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-03-11T18:20:13Z","cross_cats_sorted":[],"title_canon_sha256":"da7ca9d740611b621077718429cd97ee38746eb014d1bb35fa7b6b176a6be2ba","abstract_canon_sha256":"91f127c29c654cf8751e3b01d08ff99f614d64c65b41ff80a3705c2418158b60"},"schema_version":"1.0"},"canonical_sha256":"f53895f9e600d3ad69bb9501ed7d016a1092709940b6e84faecee5ae1dfaf38c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:48:52.384262Z","signature_b64":"lSEpzFj81l+d5eqDqUA/x9lQtPhLNm8iLl++htnC2T8GDa6/vdS0Ex6dfe/V13wTdUt/9W1jvBrOunXtkKmiAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f53895f9e600d3ad69bb9501ed7d016a1092709940b6e84faecee5ae1dfaf38c","last_reissued_at":"2026-05-18T00:48:52.383600Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:48:52.383600Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1703.04009","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":"2026-05-18T00:48:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QWdiV4FcU+Um/wZ21DhANVTYiJBy0RGkm8NIi/RV+CNJcLQs+J75UF+NIcJOIpvBz0RdrOmyMM4tAO95fPvrDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T03:49:11.090512Z"},"content_sha256":"638aae88f4a4bce73c79bcbd22a03cbdcfbdb3fa5fc7430430d8ee49c94e283a","schema_version":"1.0","event_id":"sha256:638aae88f4a4bce73c79bcbd22a03cbdcfbdb3fa5fc7430430d8ee49c94e283a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:6U4JL6PGADJ222N3SUA627IBNI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Automated Hate Speech Detection and the Problem of Offensive Language","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dana Warmsley, Ingmar Weber, Michael Macy, Thomas Davidson","submitted_at":"2017-03-11T18:20:13Z","abstract_excerpt":"A key challenge for automatic hate-speech detection on social media is the separation of hate speech from other instances of offensive language. Lexical detection methods tend to have low precision because they classify all messages containing particular terms as hate speech and previous work using supervised learning has failed to distinguish between the two categories. We used a crowd-sourced hate speech lexicon to collect tweets containing hate speech keywords. We use crowd-sourcing to label a sample of these tweets into three categories: those containing hate speech, only offensive languag"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.04009","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":""},"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":"2026-05-18T00:48:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lokUT4R34LtaocNncdCaPwHjYB8OLz8Crhlg/fuLxnCDJN+3trOnNX0FJy7aWmMa/qQqjxkz5r2sKqAjvIrSBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T03:49:11.091045Z"},"content_sha256":"67a61828ea79738b256db3e068cbeafbecb73cf7aede19517944ea920ccb29f4","schema_version":"1.0","event_id":"sha256:67a61828ea79738b256db3e068cbeafbecb73cf7aede19517944ea920ccb29f4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6U4JL6PGADJ222N3SUA627IBNI/bundle.json","state_url":"https://pith.science/pith/6U4JL6PGADJ222N3SUA627IBNI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6U4JL6PGADJ222N3SUA627IBNI/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":"2026-06-26T03:49:11Z","links":{"resolver":"https://pith.science/pith/6U4JL6PGADJ222N3SUA627IBNI","bundle":"https://pith.science/pith/6U4JL6PGADJ222N3SUA627IBNI/bundle.json","state":"https://pith.science/pith/6U4JL6PGADJ222N3SUA627IBNI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6U4JL6PGADJ222N3SUA627IBNI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:6U4JL6PGADJ222N3SUA627IBNI","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":"91f127c29c654cf8751e3b01d08ff99f614d64c65b41ff80a3705c2418158b60","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-03-11T18:20:13Z","title_canon_sha256":"da7ca9d740611b621077718429cd97ee38746eb014d1bb35fa7b6b176a6be2ba"},"schema_version":"1.0","source":{"id":"1703.04009","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.04009","created_at":"2026-05-18T00:48:52Z"},{"alias_kind":"arxiv_version","alias_value":"1703.04009v1","created_at":"2026-05-18T00:48:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.04009","created_at":"2026-05-18T00:48:52Z"},{"alias_kind":"pith_short_12","alias_value":"6U4JL6PGADJ2","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_16","alias_value":"6U4JL6PGADJ222N3","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_8","alias_value":"6U4JL6PG","created_at":"2026-05-18T12:31:03Z"}],"graph_snapshots":[{"event_id":"sha256:67a61828ea79738b256db3e068cbeafbecb73cf7aede19517944ea920ccb29f4","target":"graph","created_at":"2026-05-18T00:48:52Z","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":"A key challenge for automatic hate-speech detection on social media is the separation of hate speech from other instances of offensive language. Lexical detection methods tend to have low precision because they classify all messages containing particular terms as hate speech and previous work using supervised learning has failed to distinguish between the two categories. We used a crowd-sourced hate speech lexicon to collect tweets containing hate speech keywords. We use crowd-sourcing to label a sample of these tweets into three categories: those containing hate speech, only offensive languag","authors_text":"Dana Warmsley, Ingmar Weber, Michael Macy, Thomas Davidson","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-03-11T18:20:13Z","title":"Automated Hate Speech Detection and the Problem of Offensive Language"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.04009","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":"sha256:638aae88f4a4bce73c79bcbd22a03cbdcfbdb3fa5fc7430430d8ee49c94e283a","target":"record","created_at":"2026-05-18T00:48:52Z","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":"91f127c29c654cf8751e3b01d08ff99f614d64c65b41ff80a3705c2418158b60","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-03-11T18:20:13Z","title_canon_sha256":"da7ca9d740611b621077718429cd97ee38746eb014d1bb35fa7b6b176a6be2ba"},"schema_version":"1.0","source":{"id":"1703.04009","kind":"arxiv","version":1}},"canonical_sha256":"f53895f9e600d3ad69bb9501ed7d016a1092709940b6e84faecee5ae1dfaf38c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f53895f9e600d3ad69bb9501ed7d016a1092709940b6e84faecee5ae1dfaf38c","first_computed_at":"2026-05-18T00:48:52.383600Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:48:52.383600Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lSEpzFj81l+d5eqDqUA/x9lQtPhLNm8iLl++htnC2T8GDa6/vdS0Ex6dfe/V13wTdUt/9W1jvBrOunXtkKmiAg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:48:52.384262Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.04009","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:638aae88f4a4bce73c79bcbd22a03cbdcfbdb3fa5fc7430430d8ee49c94e283a","sha256:67a61828ea79738b256db3e068cbeafbecb73cf7aede19517944ea920ccb29f4"],"state_sha256":"2b62fb1c88cf7778e2c9a1b1abfd7948b0351a50ef9916e5443ddd797420b61b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WPu8+OeLH3upsB+NmRqCGboBlTmYBrnolpPmBvOuKWCDmFIiZ9t+Fr0FqQHwboOpbdjiZgjzTz5Y7lBnUkw/Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T03:49:11.093442Z","bundle_sha256":"36a42a80f82805b295256bd23fd3f95b9703ee282cb663356192870072de9451"}}