{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:HW345UUIQDN5LV55KIJEYX2XQF","short_pith_number":"pith:HW345UUI","canonical_record":{"source":{"id":"1807.04990","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-07-13T10:01:19Z","cross_cats_sorted":[],"title_canon_sha256":"4b18f0d24af6574163f66460163988f17067426819fdebdfee77bfb9f7e7720a","abstract_canon_sha256":"85dcc9556ecb44736616e4ee931b65f6fd99e8315916c73d2b359c56bd55dabd"},"schema_version":"1.0"},"canonical_sha256":"3db7ced28880dbd5d7bd52124c5f5781584b3d08f3efca5996ca4b228a598eb8","source":{"kind":"arxiv","id":"1807.04990","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.04990","created_at":"2026-05-18T00:10:49Z"},{"alias_kind":"arxiv_version","alias_value":"1807.04990v1","created_at":"2026-05-18T00:10:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.04990","created_at":"2026-05-18T00:10:49Z"},{"alias_kind":"pith_short_12","alias_value":"HW345UUIQDN5","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HW345UUIQDN5LV55","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HW345UUI","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:HW345UUIQDN5LV55KIJEYX2XQF","target":"record","payload":{"canonical_record":{"source":{"id":"1807.04990","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-07-13T10:01:19Z","cross_cats_sorted":[],"title_canon_sha256":"4b18f0d24af6574163f66460163988f17067426819fdebdfee77bfb9f7e7720a","abstract_canon_sha256":"85dcc9556ecb44736616e4ee931b65f6fd99e8315916c73d2b359c56bd55dabd"},"schema_version":"1.0"},"canonical_sha256":"3db7ced28880dbd5d7bd52124c5f5781584b3d08f3efca5996ca4b228a598eb8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:10:49.274571Z","signature_b64":"WSWH1TqeAku3i46T56EHeJNPSVJ3WDtRRICsmRM4zApfRg63XezdVuOuA+/bPqsMED1zxtOdlgpxdTxAgwX6Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3db7ced28880dbd5d7bd52124c5f5781584b3d08f3efca5996ca4b228a598eb8","last_reissued_at":"2026-05-18T00:10:49.274042Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:10:49.274042Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1807.04990","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":"2026-05-18T00:10:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DxSo4RpHLdCxUkny7SofQmLFwrtK72h2XuVIdKCL+89E/RkSS/Mb1H9e9EItnmzW7dmb0SbRBhxWVlKktgsIBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T17:43:23.796420Z"},"content_sha256":"75babb8518055d0ca18d92507d5278ff507850bf8da4b93cc9931415a3a405aa","schema_version":"1.0","event_id":"sha256:75babb8518055d0ca18d92507d5278ff507850bf8da4b93cc9931415a3a405aa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:HW345UUIQDN5LV55KIJEYX2XQF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Multi-sentiment-resource Enhanced Attention Network for Sentiment Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Min Yang, Yi Liu, Yujiu Yang, Zeyang Lei","submitted_at":"2018-07-13T10:01:19Z","abstract_excerpt":"Deep learning approaches for sentiment classification do not fully exploit sentiment linguistic knowledge. In this paper, we propose a Multi-sentiment-resource Enhanced Attention Network (MEAN) to alleviate the problem by integrating three kinds of sentiment linguistic knowledge (e.g., sentiment lexicon, negation words, intensity words) into the deep neural network via attention mechanisms. By using various types of sentiment resources, MEAN utilizes sentiment-relevant information from different representation subspaces, which makes it more effective to capture the overall semantics of the sen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.04990","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":"2026-05-18T00:10:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jM4jv3e3vWpuOut06X0v8XcuutIovI8ApiM8FcMKPSBm0RTJHFtR1xm9GTt8Al80vS5yN8QFOGK9cc3pAIIBDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T17:43:23.796831Z"},"content_sha256":"3d7ec91cc4f321ca7895afee1b0d4b00ec19ae5d1bbc6d61a30f842bceff5c02","schema_version":"1.0","event_id":"sha256:3d7ec91cc4f321ca7895afee1b0d4b00ec19ae5d1bbc6d61a30f842bceff5c02"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HW345UUIQDN5LV55KIJEYX2XQF/bundle.json","state_url":"https://pith.science/pith/HW345UUIQDN5LV55KIJEYX2XQF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HW345UUIQDN5LV55KIJEYX2XQF/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":"2026-05-28T17:43:23Z","links":{"resolver":"https://pith.science/pith/HW345UUIQDN5LV55KIJEYX2XQF","bundle":"https://pith.science/pith/HW345UUIQDN5LV55KIJEYX2XQF/bundle.json","state":"https://pith.science/pith/HW345UUIQDN5LV55KIJEYX2XQF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HW345UUIQDN5LV55KIJEYX2XQF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:HW345UUIQDN5LV55KIJEYX2XQF","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":"85dcc9556ecb44736616e4ee931b65f6fd99e8315916c73d2b359c56bd55dabd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-07-13T10:01:19Z","title_canon_sha256":"4b18f0d24af6574163f66460163988f17067426819fdebdfee77bfb9f7e7720a"},"schema_version":"1.0","source":{"id":"1807.04990","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.04990","created_at":"2026-05-18T00:10:49Z"},{"alias_kind":"arxiv_version","alias_value":"1807.04990v1","created_at":"2026-05-18T00:10:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.04990","created_at":"2026-05-18T00:10:49Z"},{"alias_kind":"pith_short_12","alias_value":"HW345UUIQDN5","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HW345UUIQDN5LV55","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HW345UUI","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:3d7ec91cc4f321ca7895afee1b0d4b00ec19ae5d1bbc6d61a30f842bceff5c02","target":"graph","created_at":"2026-05-18T00:10:49Z","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":"Deep learning approaches for sentiment classification do not fully exploit sentiment linguistic knowledge. In this paper, we propose a Multi-sentiment-resource Enhanced Attention Network (MEAN) to alleviate the problem by integrating three kinds of sentiment linguistic knowledge (e.g., sentiment lexicon, negation words, intensity words) into the deep neural network via attention mechanisms. By using various types of sentiment resources, MEAN utilizes sentiment-relevant information from different representation subspaces, which makes it more effective to capture the overall semantics of the sen","authors_text":"Min Yang, Yi Liu, Yujiu Yang, Zeyang Lei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-07-13T10:01:19Z","title":"A Multi-sentiment-resource Enhanced Attention Network for Sentiment Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.04990","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":"sha256:75babb8518055d0ca18d92507d5278ff507850bf8da4b93cc9931415a3a405aa","target":"record","created_at":"2026-05-18T00:10:49Z","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":"85dcc9556ecb44736616e4ee931b65f6fd99e8315916c73d2b359c56bd55dabd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-07-13T10:01:19Z","title_canon_sha256":"4b18f0d24af6574163f66460163988f17067426819fdebdfee77bfb9f7e7720a"},"schema_version":"1.0","source":{"id":"1807.04990","kind":"arxiv","version":1}},"canonical_sha256":"3db7ced28880dbd5d7bd52124c5f5781584b3d08f3efca5996ca4b228a598eb8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3db7ced28880dbd5d7bd52124c5f5781584b3d08f3efca5996ca4b228a598eb8","first_computed_at":"2026-05-18T00:10:49.274042Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:10:49.274042Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WSWH1TqeAku3i46T56EHeJNPSVJ3WDtRRICsmRM4zApfRg63XezdVuOuA+/bPqsMED1zxtOdlgpxdTxAgwX6Aw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:10:49.274571Z","signed_message":"canonical_sha256_bytes"},"source_id":"1807.04990","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:75babb8518055d0ca18d92507d5278ff507850bf8da4b93cc9931415a3a405aa","sha256:3d7ec91cc4f321ca7895afee1b0d4b00ec19ae5d1bbc6d61a30f842bceff5c02"],"state_sha256":"c1207a7bfe40ce8b77b6f23d12e3c0373993792ed13a102c33cb48af57d96f46"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zjrPDcjiJNXobp1NNV5LlPRa7mLo9eCUam97dmUfIgHZdVkJgIAlMfjOrI1A1Z4pO+6eYMvos0Y2dxyTbNK2AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T17:43:23.800306Z","bundle_sha256":"3a94c918942d7ea623dc357d98d93ccc5c9351836313b605beec1014bf8a2a55"}}