{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:HKREZUKYETGOTV5IBGVUWDSATQ","short_pith_number":"pith:HKREZUKY","canonical_record":{"source":{"id":"1806.00674","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-02T17:18:06Z","cross_cats_sorted":[],"title_canon_sha256":"82a7a066eb912a85cec91e1f916fcf2def1581d92d82a5bb941debe47bacf6b1","abstract_canon_sha256":"38b3b8455af024cc214325abed56a0ee68a71d3a06410c230975cfe78f83ce8a"},"schema_version":"1.0"},"canonical_sha256":"3aa24cd15824cce9d7a809ab4b0e409c02a6c15171f68d1c5d8e6d9b77cab1ea","source":{"kind":"arxiv","id":"1806.00674","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.00674","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"arxiv_version","alias_value":"1806.00674v1","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.00674","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"pith_short_12","alias_value":"HKREZUKYETGO","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HKREZUKYETGOTV5I","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HKREZUKY","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:HKREZUKYETGOTV5IBGVUWDSATQ","target":"record","payload":{"canonical_record":{"source":{"id":"1806.00674","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-02T17:18:06Z","cross_cats_sorted":[],"title_canon_sha256":"82a7a066eb912a85cec91e1f916fcf2def1581d92d82a5bb941debe47bacf6b1","abstract_canon_sha256":"38b3b8455af024cc214325abed56a0ee68a71d3a06410c230975cfe78f83ce8a"},"schema_version":"1.0"},"canonical_sha256":"3aa24cd15824cce9d7a809ab4b0e409c02a6c15171f68d1c5d8e6d9b77cab1ea","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:18.769815Z","signature_b64":"QzZgRgS3LKRRGDP8Rtr+lMxmIkCgbaGFD7KumN7QQ29ah+WFwx66teapxgGzeMK59fB2kLZfsLvEr0w5dR1qAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3aa24cd15824cce9d7a809ab4b0e409c02a6c15171f68d1c5d8e6d9b77cab1ea","last_reissued_at":"2026-05-18T00:14:18.769211Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:18.769211Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.00674","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":"2026-05-18T00:14:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fDHREcGjJOFYnnvuycULZX9A5be0kVROTjB3Kq9cEBEnkNdjJjYY0OWAelhnjYq8oByCouplW0yAGUs/6UYtBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T18:51:57.805707Z"},"content_sha256":"198767f26aa14369862da0078f43debdfb399557b4fa29a7b8b7435df7f54784","schema_version":"1.0","event_id":"sha256:198767f26aa14369862da0078f43debdfb399557b4fa29a7b8b7435df7f54784"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:HKREZUKYETGOTV5IBGVUWDSATQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Emotion Detection in Text: a Review","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Armin Seyeditabari, Narges Tabari, Wlodek Zadrozny","submitted_at":"2018-06-02T17:18:06Z","abstract_excerpt":"In recent years, emotion detection in text has become more popular due to its vast potential applications in marketing, political science, psychology, human-computer interaction, artificial intelligence, etc. Access to a huge amount of textual data, especially opinionated and self-expression text also played a special role to bring attention to this field. In this paper, we review the work that has been done in identifying emotion expressions in text and argue that although many techniques, methodologies, and models have been created to detect emotion in text, there are various reasons that ma"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.00674","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":"2026-05-18T00:14:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MjE23BJP3Th2QfsoD/4UP4OTYr7Hq+9/BxV2wuTiDhWsfHtLBh4B51D7b2B+1ZPUoO6NkrIxlyJOz57TDhhLDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T18:51:57.806053Z"},"content_sha256":"0fcb1714c61761678f694dbc6f80f095e32052272d1a97a31e259d86b70e80e3","schema_version":"1.0","event_id":"sha256:0fcb1714c61761678f694dbc6f80f095e32052272d1a97a31e259d86b70e80e3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HKREZUKYETGOTV5IBGVUWDSATQ/bundle.json","state_url":"https://pith.science/pith/HKREZUKYETGOTV5IBGVUWDSATQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HKREZUKYETGOTV5IBGVUWDSATQ/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":"2026-06-28T18:51:57Z","links":{"resolver":"https://pith.science/pith/HKREZUKYETGOTV5IBGVUWDSATQ","bundle":"https://pith.science/pith/HKREZUKYETGOTV5IBGVUWDSATQ/bundle.json","state":"https://pith.science/pith/HKREZUKYETGOTV5IBGVUWDSATQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HKREZUKYETGOTV5IBGVUWDSATQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:HKREZUKYETGOTV5IBGVUWDSATQ","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":"38b3b8455af024cc214325abed56a0ee68a71d3a06410c230975cfe78f83ce8a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-02T17:18:06Z","title_canon_sha256":"82a7a066eb912a85cec91e1f916fcf2def1581d92d82a5bb941debe47bacf6b1"},"schema_version":"1.0","source":{"id":"1806.00674","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.00674","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"arxiv_version","alias_value":"1806.00674v1","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.00674","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"pith_short_12","alias_value":"HKREZUKYETGO","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HKREZUKYETGOTV5I","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HKREZUKY","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:0fcb1714c61761678f694dbc6f80f095e32052272d1a97a31e259d86b70e80e3","target":"graph","created_at":"2026-05-18T00:14:18Z","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":"In recent years, emotion detection in text has become more popular due to its vast potential applications in marketing, political science, psychology, human-computer interaction, artificial intelligence, etc. Access to a huge amount of textual data, especially opinionated and self-expression text also played a special role to bring attention to this field. In this paper, we review the work that has been done in identifying emotion expressions in text and argue that although many techniques, methodologies, and models have been created to detect emotion in text, there are various reasons that ma","authors_text":"Armin Seyeditabari, Narges Tabari, Wlodek Zadrozny","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-02T17:18:06Z","title":"Emotion Detection in Text: a Review"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.00674","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":"sha256:198767f26aa14369862da0078f43debdfb399557b4fa29a7b8b7435df7f54784","target":"record","created_at":"2026-05-18T00:14:18Z","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":"38b3b8455af024cc214325abed56a0ee68a71d3a06410c230975cfe78f83ce8a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-02T17:18:06Z","title_canon_sha256":"82a7a066eb912a85cec91e1f916fcf2def1581d92d82a5bb941debe47bacf6b1"},"schema_version":"1.0","source":{"id":"1806.00674","kind":"arxiv","version":1}},"canonical_sha256":"3aa24cd15824cce9d7a809ab4b0e409c02a6c15171f68d1c5d8e6d9b77cab1ea","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3aa24cd15824cce9d7a809ab4b0e409c02a6c15171f68d1c5d8e6d9b77cab1ea","first_computed_at":"2026-05-18T00:14:18.769211Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:18.769211Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QzZgRgS3LKRRGDP8Rtr+lMxmIkCgbaGFD7KumN7QQ29ah+WFwx66teapxgGzeMK59fB2kLZfsLvEr0w5dR1qAg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:18.769815Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.00674","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:198767f26aa14369862da0078f43debdfb399557b4fa29a7b8b7435df7f54784","sha256:0fcb1714c61761678f694dbc6f80f095e32052272d1a97a31e259d86b70e80e3"],"state_sha256":"5559fdf5fa6ea1758bf8bca75d27d805d4da7372a6d4d80221c75cc55e489dca"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8CjI3j3N0SfRQVjiCVwYm7cqKc4XzkvvU9cEvuRn0R9h9zMJabgfWbQrAumHdA6rw4oJBhDSbrzic6uKJB49Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-28T18:51:57.808064Z","bundle_sha256":"ffdbf106920ec3c1f1e7052ea725db2721e9ed451bdeeab7a9f7979c4631ade6"}}