{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:MEFBOUOBRQQCPRU2CBVOCMKFTD","short_pith_number":"pith:MEFBOUOB","schema_version":"1.0","canonical_sha256":"610a1751c18c2027c69a106ae1314598cced2832c3d1b7636c07593ffb1c6856","source":{"kind":"arxiv","id":"2411.12196","version":2},"attestation_state":"computed","paper":{"title":"A More Advanced Group Polarization Measurement Approach Based on LLM-Based Agents and Graphs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CY","authors_text":"Ji Zhang, Yiran Ding, Zixin Liu","submitted_at":"2024-11-19T03:29:17Z","abstract_excerpt":"Group polarization is an important research direction in social media content analysis, attracting many researchers to explore this field. Therefore, how to effectively measure group polarization has become a critical topic. Measuring group polarization on social media presents several challenges that have not yet been addressed by existing solutions. First, social media group polarization measurement involves processing vast amounts of text, which poses a significant challenge for information extraction. Second, social media texts often contain hard-to-understand content, including sarcasm, m"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2411.12196","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-11-19T03:29:17Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"bfa905bbe09475a0b73244b1ef42a78753e2d3797ae42bc928da9cde45173137","abstract_canon_sha256":"53cd646e7b67db94758fd20800392d394d1bc06718c0e9758c89eeba314eb815"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:49:46.361387Z","signature_b64":"xwnCO2QLgNcbyc32vB477FYF5jF0mG/ay4TW0i4pimQEibKBykVpRE+XXN2yDipHvnnNYq9/wm0Z44Nk/yvFCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"610a1751c18c2027c69a106ae1314598cced2832c3d1b7636c07593ffb1c6856","last_reissued_at":"2026-07-05T09:49:46.360966Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:49:46.360966Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A More Advanced Group Polarization Measurement Approach Based on LLM-Based Agents and Graphs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CY","authors_text":"Ji Zhang, Yiran Ding, Zixin Liu","submitted_at":"2024-11-19T03:29:17Z","abstract_excerpt":"Group polarization is an important research direction in social media content analysis, attracting many researchers to explore this field. Therefore, how to effectively measure group polarization has become a critical topic. Measuring group polarization on social media presents several challenges that have not yet been addressed by existing solutions. First, social media group polarization measurement involves processing vast amounts of text, which poses a significant challenge for information extraction. Second, social media texts often contain hard-to-understand content, including sarcasm, m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.12196","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/2411.12196/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2411.12196","created_at":"2026-07-05T09:49:46.361023+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.12196v2","created_at":"2026-07-05T09:49:46.361023+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.12196","created_at":"2026-07-05T09:49:46.361023+00:00"},{"alias_kind":"pith_short_12","alias_value":"MEFBOUOBRQQC","created_at":"2026-07-05T09:49:46.361023+00:00"},{"alias_kind":"pith_short_16","alias_value":"MEFBOUOBRQQCPRU2","created_at":"2026-07-05T09:49:46.361023+00:00"},{"alias_kind":"pith_short_8","alias_value":"MEFBOUOB","created_at":"2026-07-05T09:49:46.361023+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/MEFBOUOBRQQCPRU2CBVOCMKFTD","json":"https://pith.science/pith/MEFBOUOBRQQCPRU2CBVOCMKFTD.json","graph_json":"https://pith.science/api/pith-number/MEFBOUOBRQQCPRU2CBVOCMKFTD/graph.json","events_json":"https://pith.science/api/pith-number/MEFBOUOBRQQCPRU2CBVOCMKFTD/events.json","paper":"https://pith.science/paper/MEFBOUOB"},"agent_actions":{"view_html":"https://pith.science/pith/MEFBOUOBRQQCPRU2CBVOCMKFTD","download_json":"https://pith.science/pith/MEFBOUOBRQQCPRU2CBVOCMKFTD.json","view_paper":"https://pith.science/paper/MEFBOUOB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.12196&json=true","fetch_graph":"https://pith.science/api/pith-number/MEFBOUOBRQQCPRU2CBVOCMKFTD/graph.json","fetch_events":"https://pith.science/api/pith-number/MEFBOUOBRQQCPRU2CBVOCMKFTD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MEFBOUOBRQQCPRU2CBVOCMKFTD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MEFBOUOBRQQCPRU2CBVOCMKFTD/action/storage_attestation","attest_author":"https://pith.science/pith/MEFBOUOBRQQCPRU2CBVOCMKFTD/action/author_attestation","sign_citation":"https://pith.science/pith/MEFBOUOBRQQCPRU2CBVOCMKFTD/action/citation_signature","submit_replication":"https://pith.science/pith/MEFBOUOBRQQCPRU2CBVOCMKFTD/action/replication_record"}},"created_at":"2026-07-05T09:49:46.361023+00:00","updated_at":"2026-07-05T09:49:46.361023+00:00"}