{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:SKBZWRQFLN7DWIUDGB6JH33BBH","short_pith_number":"pith:SKBZWRQF","canonical_record":{"source":{"id":"2309.13731","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-24T19:26:53Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"00605adcf18696072b8179bdec1bf5e591132b848c8a4cf282438560bcf04628","abstract_canon_sha256":"677c7a0db2ac7f3f3224ffb54bc943ea5a5be53ecd230965dbe08401154d92d6"},"schema_version":"1.0"},"canonical_sha256":"92839b46055b7e3b2283307c93ef6109e0fc53c8f34d1e5d1a6b5fdc7fa7b448","source":{"kind":"arxiv","id":"2309.13731","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.13731","created_at":"2026-07-05T08:49:25Z"},{"alias_kind":"arxiv_version","alias_value":"2309.13731v2","created_at":"2026-07-05T08:49:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.13731","created_at":"2026-07-05T08:49:25Z"},{"alias_kind":"pith_short_12","alias_value":"SKBZWRQFLN7D","created_at":"2026-07-05T08:49:25Z"},{"alias_kind":"pith_short_16","alias_value":"SKBZWRQFLN7DWIUD","created_at":"2026-07-05T08:49:25Z"},{"alias_kind":"pith_short_8","alias_value":"SKBZWRQF","created_at":"2026-07-05T08:49:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:SKBZWRQFLN7DWIUDGB6JH33BBH","target":"record","payload":{"canonical_record":{"source":{"id":"2309.13731","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-24T19:26:53Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"00605adcf18696072b8179bdec1bf5e591132b848c8a4cf282438560bcf04628","abstract_canon_sha256":"677c7a0db2ac7f3f3224ffb54bc943ea5a5be53ecd230965dbe08401154d92d6"},"schema_version":"1.0"},"canonical_sha256":"92839b46055b7e3b2283307c93ef6109e0fc53c8f34d1e5d1a6b5fdc7fa7b448","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:49:25.769840Z","signature_b64":"AmKNyZnfWmd6FHzjFJAE7wbl9ZRRqqnx4XKV6Zfr508T9GKqbOqEWP3WRCJyxhKCGDx/r/44B2A5v9HKVQAdAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"92839b46055b7e3b2283307c93ef6109e0fc53c8f34d1e5d1a6b5fdc7fa7b448","last_reissued_at":"2026-07-05T08:49:25.769424Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:49:25.769424Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2309.13731","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:49:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sSfZM0TwaQANIRS0Rw/dOg5bSUSzpFr63Lb7b11mc7KF/9JqfrEVrxLO43u4XpC3tKMwpSPwKM84inlwzHfMBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T21:28:07.902555Z"},"content_sha256":"4e08f912136ca8f7c56b9a8199ccbab754405d11bd5690509f93f9ab37042e55","schema_version":"1.0","event_id":"sha256:4e08f912136ca8f7c56b9a8199ccbab754405d11bd5690509f93f9ab37042e55"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:SKBZWRQFLN7DWIUDGB6JH33BBH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Arabic Sentiment Analysis with Noisy Deep Explainable Model","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Alexander Boden, Maksuda Bilkis Baby, Md. Atabuzzaman, Md Shajalal","submitted_at":"2023-09-24T19:26:53Z","abstract_excerpt":"Sentiment Analysis (SA) is an indispensable task for many real-world applications. Compared to limited resourced languages (i.e., Arabic, Bengali), most of the research on SA are conducted for high resourced languages (i.e., English, Chinese). Moreover, the reasons behind any prediction of the Arabic sentiment analysis methods exploiting advanced artificial intelligence (AI)-based approaches are like black-box - quite difficult to understand. This paper proposes an explainable sentiment classification framework for the Arabic language by introducing a noise layer on Bi-Directional Long Short-T"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.13731","kind":"arxiv","version":2},"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/2309.13731/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":"2026-07-05T08:49:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LP0IIpudaSwK1esscFNfwV1IbAjhBoPD1IMp75D64Q+00tsDBNHzwOGDlscoDorh6kFOm5QXt29gVOZcDhLwCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T21:28:07.903475Z"},"content_sha256":"e672521cbe6c733ab2434f84e310ec6e202ec9b00d53998e9c4a527d70462bd4","schema_version":"1.0","event_id":"sha256:e672521cbe6c733ab2434f84e310ec6e202ec9b00d53998e9c4a527d70462bd4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SKBZWRQFLN7DWIUDGB6JH33BBH/bundle.json","state_url":"https://pith.science/pith/SKBZWRQFLN7DWIUDGB6JH33BBH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SKBZWRQFLN7DWIUDGB6JH33BBH/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":"2026-08-19T21:28:07Z","links":{"resolver":"https://pith.science/pith/SKBZWRQFLN7DWIUDGB6JH33BBH","bundle":"https://pith.science/pith/SKBZWRQFLN7DWIUDGB6JH33BBH/bundle.json","state":"https://pith.science/pith/SKBZWRQFLN7DWIUDGB6JH33BBH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SKBZWRQFLN7DWIUDGB6JH33BBH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:SKBZWRQFLN7DWIUDGB6JH33BBH","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":"677c7a0db2ac7f3f3224ffb54bc943ea5a5be53ecd230965dbe08401154d92d6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-24T19:26:53Z","title_canon_sha256":"00605adcf18696072b8179bdec1bf5e591132b848c8a4cf282438560bcf04628"},"schema_version":"1.0","source":{"id":"2309.13731","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.13731","created_at":"2026-07-05T08:49:25Z"},{"alias_kind":"arxiv_version","alias_value":"2309.13731v2","created_at":"2026-07-05T08:49:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.13731","created_at":"2026-07-05T08:49:25Z"},{"alias_kind":"pith_short_12","alias_value":"SKBZWRQFLN7D","created_at":"2026-07-05T08:49:25Z"},{"alias_kind":"pith_short_16","alias_value":"SKBZWRQFLN7DWIUD","created_at":"2026-07-05T08:49:25Z"},{"alias_kind":"pith_short_8","alias_value":"SKBZWRQF","created_at":"2026-07-05T08:49:25Z"}],"graph_snapshots":[{"event_id":"sha256:e672521cbe6c733ab2434f84e310ec6e202ec9b00d53998e9c4a527d70462bd4","target":"graph","created_at":"2026-07-05T08:49:25Z","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/2309.13731/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sentiment Analysis (SA) is an indispensable task for many real-world applications. Compared to limited resourced languages (i.e., Arabic, Bengali), most of the research on SA are conducted for high resourced languages (i.e., English, Chinese). Moreover, the reasons behind any prediction of the Arabic sentiment analysis methods exploiting advanced artificial intelligence (AI)-based approaches are like black-box - quite difficult to understand. This paper proposes an explainable sentiment classification framework for the Arabic language by introducing a noise layer on Bi-Directional Long Short-T","authors_text":"Alexander Boden, Maksuda Bilkis Baby, Md. Atabuzzaman, Md Shajalal","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-24T19:26:53Z","title":"Arabic Sentiment Analysis with Noisy Deep Explainable Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.13731","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":"sha256:4e08f912136ca8f7c56b9a8199ccbab754405d11bd5690509f93f9ab37042e55","target":"record","created_at":"2026-07-05T08:49:25Z","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":"677c7a0db2ac7f3f3224ffb54bc943ea5a5be53ecd230965dbe08401154d92d6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-24T19:26:53Z","title_canon_sha256":"00605adcf18696072b8179bdec1bf5e591132b848c8a4cf282438560bcf04628"},"schema_version":"1.0","source":{"id":"2309.13731","kind":"arxiv","version":2}},"canonical_sha256":"92839b46055b7e3b2283307c93ef6109e0fc53c8f34d1e5d1a6b5fdc7fa7b448","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"92839b46055b7e3b2283307c93ef6109e0fc53c8f34d1e5d1a6b5fdc7fa7b448","first_computed_at":"2026-07-05T08:49:25.769424Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:49:25.769424Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AmKNyZnfWmd6FHzjFJAE7wbl9ZRRqqnx4XKV6Zfr508T9GKqbOqEWP3WRCJyxhKCGDx/r/44B2A5v9HKVQAdAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:49:25.769840Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.13731","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e08f912136ca8f7c56b9a8199ccbab754405d11bd5690509f93f9ab37042e55","sha256:e672521cbe6c733ab2434f84e310ec6e202ec9b00d53998e9c4a527d70462bd4"],"state_sha256":"33c04404261c996347cba481fd8a797dcb8cc334367243b6cf322dffd79b92d5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NJEEnNtCGbPmj0+t4ecx0Tlww7ZIqlbIwB0FvaJqycyp1Hhna/s8ZkM64S55Fs2AVs8mQoaVG6ud1ByvxYQJAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T21:28:07.949303Z","bundle_sha256":"17d2569d0866cb475b6acd148ba3bce9c75ba3ce2c5c3ba33af7b4cbdddfc201"}}