{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:HVX4NE3XVDTDZIUSZDNVMDD6IV","short_pith_number":"pith:HVX4NE3X","canonical_record":{"source":{"id":"1907.07826","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-18T01:00:42Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b1b9e2f39aa09f60709f1951a2e73100548649d0be8588539c93fc2dab29d152","abstract_canon_sha256":"5be2049cb873f6a6d3d2379076c18d9b1e45baa75f382a90a4d652fa1fb619c6"},"schema_version":"1.0"},"canonical_sha256":"3d6fc69377a8e63ca292c8db560c7e454ad0d0b11b971072064cea8a82d7ce73","source":{"kind":"arxiv","id":"1907.07826","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.07826","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"arxiv_version","alias_value":"1907.07826v1","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.07826","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"pith_short_12","alias_value":"HVX4NE3XVDTD","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"HVX4NE3XVDTDZIUS","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"HVX4NE3X","created_at":"2026-05-18T12:33:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:HVX4NE3XVDTDZIUSZDNVMDD6IV","target":"record","payload":{"canonical_record":{"source":{"id":"1907.07826","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-18T01:00:42Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b1b9e2f39aa09f60709f1951a2e73100548649d0be8588539c93fc2dab29d152","abstract_canon_sha256":"5be2049cb873f6a6d3d2379076c18d9b1e45baa75f382a90a4d652fa1fb619c6"},"schema_version":"1.0"},"canonical_sha256":"3d6fc69377a8e63ca292c8db560c7e454ad0d0b11b971072064cea8a82d7ce73","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:16.132107Z","signature_b64":"JbDDzOXlUEYRhbxIILAkkR/9WFZ0LJP+Q18TJPxymKtaUom/GGAOEE+CzUjzVo54A7xDtQuiPSdMBWhDkmBLCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3d6fc69377a8e63ca292c8db560c7e454ad0d0b11b971072064cea8a82d7ce73","last_reissued_at":"2026-05-17T23:40:16.131337Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:16.131337Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.07826","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":"2026-05-17T23:40:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X6Zt+JZ2G7J1cwm+6Iu6fZuRGPAPAGqopFHLL0BNK9Gwc/AdrV/3q6MyL+7f6+sHncx46a53cK5z+eRxhgJ2Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T07:55:19.334189Z"},"content_sha256":"f84fdcd42040bfcb3e0cbb295b845d4baa2523ccd2bd04ed1e6b2e9f5c26be9c","schema_version":"1.0","event_id":"sha256:f84fdcd42040bfcb3e0cbb295b845d4baa2523ccd2bd04ed1e6b2e9f5c26be9c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:HVX4NE3XVDTDZIUSZDNVMDD6IV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Comparison of Classical Machine Learning Approaches on Bangla Textual Emotion Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Md. Ataur Rahman, Md. Hanif Seddiqui","submitted_at":"2019-07-18T01:00:42Z","abstract_excerpt":"Detecting emotions from text is an extension of simple sentiment polarity detection. Instead of considering only positive or negative sentiments, emotions are conveyed using more tangible manner; thus, they can be expressed as many shades of gray. This paper manifests the results of our experimentation for fine-grained emotion analysis on Bangla text. We gathered and annotated a text corpus consisting of user comments from several Facebook groups regarding socio-economic and political issues, and we made efforts to extract the basic emotions (sadness, happiness, disgust, surprise, fear, anger)"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.07826","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":"2026-05-17T23:40:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VQT2diizs+BUoHWnE86VFjtO2ZxtR8OB8oLbXmOb8ZBCw495I50aWl1gXQdvYt4IPt3pORMiozviH0neGFOhAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T07:55:19.334969Z"},"content_sha256":"5d9d2ac4442f4ebf074902bfd7447d7ae379a7fb15887ce4f02daecf2320324b","schema_version":"1.0","event_id":"sha256:5d9d2ac4442f4ebf074902bfd7447d7ae379a7fb15887ce4f02daecf2320324b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HVX4NE3XVDTDZIUSZDNVMDD6IV/bundle.json","state_url":"https://pith.science/pith/HVX4NE3XVDTDZIUSZDNVMDD6IV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HVX4NE3XVDTDZIUSZDNVMDD6IV/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":"2026-06-11T07:55:19Z","links":{"resolver":"https://pith.science/pith/HVX4NE3XVDTDZIUSZDNVMDD6IV","bundle":"https://pith.science/pith/HVX4NE3XVDTDZIUSZDNVMDD6IV/bundle.json","state":"https://pith.science/pith/HVX4NE3XVDTDZIUSZDNVMDD6IV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HVX4NE3XVDTDZIUSZDNVMDD6IV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:HVX4NE3XVDTDZIUSZDNVMDD6IV","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":"5be2049cb873f6a6d3d2379076c18d9b1e45baa75f382a90a4d652fa1fb619c6","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-18T01:00:42Z","title_canon_sha256":"b1b9e2f39aa09f60709f1951a2e73100548649d0be8588539c93fc2dab29d152"},"schema_version":"1.0","source":{"id":"1907.07826","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.07826","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"arxiv_version","alias_value":"1907.07826v1","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.07826","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"pith_short_12","alias_value":"HVX4NE3XVDTD","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"HVX4NE3XVDTDZIUS","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"HVX4NE3X","created_at":"2026-05-18T12:33:18Z"}],"graph_snapshots":[{"event_id":"sha256:5d9d2ac4442f4ebf074902bfd7447d7ae379a7fb15887ce4f02daecf2320324b","target":"graph","created_at":"2026-05-17T23:40:16Z","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":"Detecting emotions from text is an extension of simple sentiment polarity detection. Instead of considering only positive or negative sentiments, emotions are conveyed using more tangible manner; thus, they can be expressed as many shades of gray. This paper manifests the results of our experimentation for fine-grained emotion analysis on Bangla text. We gathered and annotated a text corpus consisting of user comments from several Facebook groups regarding socio-economic and political issues, and we made efforts to extract the basic emotions (sadness, happiness, disgust, surprise, fear, anger)","authors_text":"Md. Ataur Rahman, Md. Hanif Seddiqui","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-18T01:00:42Z","title":"Comparison of Classical Machine Learning Approaches on Bangla Textual Emotion Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.07826","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:f84fdcd42040bfcb3e0cbb295b845d4baa2523ccd2bd04ed1e6b2e9f5c26be9c","target":"record","created_at":"2026-05-17T23:40:16Z","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":"5be2049cb873f6a6d3d2379076c18d9b1e45baa75f382a90a4d652fa1fb619c6","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-18T01:00:42Z","title_canon_sha256":"b1b9e2f39aa09f60709f1951a2e73100548649d0be8588539c93fc2dab29d152"},"schema_version":"1.0","source":{"id":"1907.07826","kind":"arxiv","version":1}},"canonical_sha256":"3d6fc69377a8e63ca292c8db560c7e454ad0d0b11b971072064cea8a82d7ce73","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3d6fc69377a8e63ca292c8db560c7e454ad0d0b11b971072064cea8a82d7ce73","first_computed_at":"2026-05-17T23:40:16.131337Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:40:16.131337Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JbDDzOXlUEYRhbxIILAkkR/9WFZ0LJP+Q18TJPxymKtaUom/GGAOEE+CzUjzVo54A7xDtQuiPSdMBWhDkmBLCw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:40:16.132107Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.07826","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f84fdcd42040bfcb3e0cbb295b845d4baa2523ccd2bd04ed1e6b2e9f5c26be9c","sha256:5d9d2ac4442f4ebf074902bfd7447d7ae379a7fb15887ce4f02daecf2320324b"],"state_sha256":"1653dcf69cbef3bd2a7aa3309cd83883ff0012a372a437df8e6ed75dc1e35407"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HuF7xSlOI6D2KU/Aq8LJNSKCc3nBUeMTT06u8cyTynyJKcnQN1AUxf3lr9qEnbp5YEhBNvgIRjchf4rCUZTZDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T07:55:19.339605Z","bundle_sha256":"3f9f478e92443a2783f914fa73f4bcedbb5c65794e293f7a36013a6abbb8e276"}}