{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:ZYFWB3J74FGOCRXVNL7LXLDETX","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":"d624d54a43afc3b3938bf377134e083bf70ec7463ceb7fbf2511dbee2e41f154","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-08-11T15:21:23Z","title_canon_sha256":"3ac12db54001f7860b4d000ec6f76c46b6d8141911be1253234ee957ee210245"},"schema_version":"1.0","source":{"id":"2608.11049","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.11049","created_at":"2026-08-12T01:24:29Z"},{"alias_kind":"arxiv_version","alias_value":"2608.11049v1","created_at":"2026-08-12T01:24:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.11049","created_at":"2026-08-12T01:24:29Z"},{"alias_kind":"pith_short_12","alias_value":"ZYFWB3J74FGO","created_at":"2026-08-12T01:24:29Z"},{"alias_kind":"pith_short_16","alias_value":"ZYFWB3J74FGOCRXV","created_at":"2026-08-12T01:24:29Z"},{"alias_kind":"pith_short_8","alias_value":"ZYFWB3J7","created_at":"2026-08-12T01:24:29Z"}],"graph_snapshots":[{"event_id":"sha256:1e5f2bf60193644b1dd93493a9c8cf01e9eb3caede8c33dd779fe93700f7b75c","target":"graph","created_at":"2026-08-12T01:24:29Z","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/2608.11049/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The rapid growth of social media has created vast amounts of political discourse, which provides valuable opportunities to analyze public opinions and identify different political perspectives. Sentiment Analysis (SA) is a core task in Natural Language Processing (NLP) that allows the computational study of attitudes and opinions in textual data, and has become increasingly important for understanding political discourse. In this work, we investigate multiclass sentiment analysis of political view- points on social media, that is to automatically discriminate multiple sentiment classes over po","authors_text":"Girma Yohannis Bade, Grigori Sidorov, Jose Luis Oropeza, Olga Kolesnikova","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-08-11T15:21:23Z","title":"Multiclass Sentiment Analysis for Identifying Political Viewpoints"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.11049","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:c4b0576ffc5bfe09c19e173ecf7b4896363b723c36c4aefc44e5153e30631a94","target":"record","created_at":"2026-08-12T01:24:29Z","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":"d624d54a43afc3b3938bf377134e083bf70ec7463ceb7fbf2511dbee2e41f154","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-08-11T15:21:23Z","title_canon_sha256":"3ac12db54001f7860b4d000ec6f76c46b6d8141911be1253234ee957ee210245"},"schema_version":"1.0","source":{"id":"2608.11049","kind":"arxiv","version":1}},"canonical_sha256":"ce0b60ed3fe14ce146f56afebbac649dd72f590a973b9c4cb5879f32dc3f1bfc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ce0b60ed3fe14ce146f56afebbac649dd72f590a973b9c4cb5879f32dc3f1bfc","first_computed_at":"2026-08-12T01:24:29.973610Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-12T01:24:29.973610Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jarBFCJBV27UfNiDWsVhEPyU4hDF3VgnX/jD7bT+GqUQ9DopSvZztlVYKbBJteIr9oo4RyOj5Kk6D8NKWZG0Bg==","signature_status":"signed_v1","signed_at":"2026-08-12T01:24:29.975443Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.11049","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c4b0576ffc5bfe09c19e173ecf7b4896363b723c36c4aefc44e5153e30631a94","sha256:1e5f2bf60193644b1dd93493a9c8cf01e9eb3caede8c33dd779fe93700f7b75c"],"state_sha256":"a42e5987036f3bedfa070c6c6c1397aa322d6de5d5eb428d2e9151f14fb2af50"}