{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:NQXFE4RF2L7W72CE4B4SCQO76A","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":"9e0ff2067b0dc7b7ecd8fce6acc06cddc93ce23cd4d22c1c4369c0df3cf216f7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2019-11-21T08:39:21Z","title_canon_sha256":"55e843632dc0b0d8fae6ffb187c08c0aaed069fe7fd97370a35cae523af9b76c"},"schema_version":"1.0","source":{"id":"1911.09339","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.09339","created_at":"2026-07-05T00:35:53Z"},{"alias_kind":"arxiv_version","alias_value":"1911.09339v2","created_at":"2026-07-05T00:35:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.09339","created_at":"2026-07-05T00:35:53Z"},{"alias_kind":"pith_short_12","alias_value":"NQXFE4RF2L7W","created_at":"2026-07-05T00:35:53Z"},{"alias_kind":"pith_short_16","alias_value":"NQXFE4RF2L7W72CE","created_at":"2026-07-05T00:35:53Z"},{"alias_kind":"pith_short_8","alias_value":"NQXFE4RF","created_at":"2026-07-05T00:35:53Z"}],"graph_snapshots":[{"event_id":"sha256:076dca773b8af298c43aaa1d513b3c32528493ab4a031b150d662266697a478f","target":"graph","created_at":"2026-07-05T00:35:53Z","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/1911.09339/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Emotion recognition or emotion prediction is a higher approach or a special case of sentiment analysis. In this task, the result is not produced in terms of either polarity: positive or negative or in the form of rating (from 1 to 5) but of a more detailed level of analysis in which the results are depicted in more expressions like sadness, enjoyment, anger, disgust, fear, and surprise. Emotion recognition plays a critical role in measuring the brand value of a product by recognizing specific emotions of customers' comments. In this study, we have achieved two targets. First and foremost, we b","authors_text":"Danh Hoang Nguyen, Duc-Vu Nguyen, Duong Huynh-Cong Nguyen, Kiet Van Nguyen, Linh Thi-Van Pham, Ngan Luu-Thuy Nguyen, Vong Anh Ho","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2019-11-21T08:39:21Z","title":"Emotion Recognition for Vietnamese Social Media Text"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.09339","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:b9b06fa3139ba34a7ea1f447f266b7f6d840fc4098dba6e6c605c827e6d04409","target":"record","created_at":"2026-07-05T00:35:53Z","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":"9e0ff2067b0dc7b7ecd8fce6acc06cddc93ce23cd4d22c1c4369c0df3cf216f7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2019-11-21T08:39:21Z","title_canon_sha256":"55e843632dc0b0d8fae6ffb187c08c0aaed069fe7fd97370a35cae523af9b76c"},"schema_version":"1.0","source":{"id":"1911.09339","kind":"arxiv","version":2}},"canonical_sha256":"6c2e527225d2ff6fe844e0792141dff020bc7b0fb877c92f659c0715c8be8ded","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6c2e527225d2ff6fe844e0792141dff020bc7b0fb877c92f659c0715c8be8ded","first_computed_at":"2026-07-05T00:35:53.833241Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:35:53.833241Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"C9vp51ubjtQgv/3zo24h2magbCtpW6AktuDQcV7eGPTTGhvmCYvJ4qEw4DlkwYyefmPY6S0EoBVpS8L16XjpBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:35:53.833765Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.09339","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b9b06fa3139ba34a7ea1f447f266b7f6d840fc4098dba6e6c605c827e6d04409","sha256:076dca773b8af298c43aaa1d513b3c32528493ab4a031b150d662266697a478f"],"state_sha256":"248349a9fedc84fd400f70f1544a72e9ad2026237329ef771678c1711018980d"}