{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:57LOPKAWNY22PWISATNGNPW7VX","short_pith_number":"pith:57LOPKAW","schema_version":"1.0","canonical_sha256":"efd6e7a8166e35a7d91204da66bedfadc519c6ad1711c6f9e3dd394c8c12c357","source":{"kind":"arxiv","id":"2101.03545","version":1},"attestation_state":"computed","paper":{"title":"A Heuristic-driven Ensemble Framework for COVID-19 Fake News Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Ayan Basak, Saikat Dutta, Sourya Dipta Das","submitted_at":"2021-01-10T13:21:08Z","abstract_excerpt":"The significance of social media has increased manifold in the past few decades as it helps people from even the most remote corners of the world stay connected. With the COVID-19 pandemic raging, social media has become more relevant and widely used than ever before, and along with this, there has been a resurgence in the circulation of fake news and tweets that demand immediate attention. In this paper, we describe our Fake News Detection system that automatically identifies whether a tweet related to COVID-19 is \"real\" or \"fake\", as a part of CONSTRAINT COVID19 Fake News Detection in Englis"},"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":"2101.03545","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-01-10T13:21:08Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f148f34c59a5666d059f9f3e4b5b633459c61373b8437a8509ec388eaf52b37f","abstract_canon_sha256":"b294cf40884ef5e1e74a83a198bc5c81ff53a00a01ba446d6d403e9670121dd0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:05:51.223242Z","signature_b64":"IJmlH5TQOOh2y5LuxPzU4M29AQINgvCST4nGKgvXvlwkusV49KCWvcrvmpWuwfLNTxTL9ZlImzW11IySzDmmCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"efd6e7a8166e35a7d91204da66bedfadc519c6ad1711c6f9e3dd394c8c12c357","last_reissued_at":"2026-07-05T02:05:51.222873Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:05:51.222873Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Heuristic-driven Ensemble Framework for COVID-19 Fake News Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Ayan Basak, Saikat Dutta, Sourya Dipta Das","submitted_at":"2021-01-10T13:21:08Z","abstract_excerpt":"The significance of social media has increased manifold in the past few decades as it helps people from even the most remote corners of the world stay connected. With the COVID-19 pandemic raging, social media has become more relevant and widely used than ever before, and along with this, there has been a resurgence in the circulation of fake news and tweets that demand immediate attention. In this paper, we describe our Fake News Detection system that automatically identifies whether a tweet related to COVID-19 is \"real\" or \"fake\", as a part of CONSTRAINT COVID19 Fake News Detection in Englis"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.03545","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2101.03545/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":"2101.03545","created_at":"2026-07-05T02:05:51.222930+00:00"},{"alias_kind":"arxiv_version","alias_value":"2101.03545v1","created_at":"2026-07-05T02:05:51.222930+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.03545","created_at":"2026-07-05T02:05:51.222930+00:00"},{"alias_kind":"pith_short_12","alias_value":"57LOPKAWNY22","created_at":"2026-07-05T02:05:51.222930+00:00"},{"alias_kind":"pith_short_16","alias_value":"57LOPKAWNY22PWIS","created_at":"2026-07-05T02:05:51.222930+00:00"},{"alias_kind":"pith_short_8","alias_value":"57LOPKAW","created_at":"2026-07-05T02:05:51.222930+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2508.21457","citing_title":"SoK: Exposing the Generation and Detection Gaps in LLM-Generated Phishing","ref_index":29,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/57LOPKAWNY22PWISATNGNPW7VX","json":"https://pith.science/pith/57LOPKAWNY22PWISATNGNPW7VX.json","graph_json":"https://pith.science/api/pith-number/57LOPKAWNY22PWISATNGNPW7VX/graph.json","events_json":"https://pith.science/api/pith-number/57LOPKAWNY22PWISATNGNPW7VX/events.json","paper":"https://pith.science/paper/57LOPKAW"},"agent_actions":{"view_html":"https://pith.science/pith/57LOPKAWNY22PWISATNGNPW7VX","download_json":"https://pith.science/pith/57LOPKAWNY22PWISATNGNPW7VX.json","view_paper":"https://pith.science/paper/57LOPKAW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2101.03545&json=true","fetch_graph":"https://pith.science/api/pith-number/57LOPKAWNY22PWISATNGNPW7VX/graph.json","fetch_events":"https://pith.science/api/pith-number/57LOPKAWNY22PWISATNGNPW7VX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/57LOPKAWNY22PWISATNGNPW7VX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/57LOPKAWNY22PWISATNGNPW7VX/action/storage_attestation","attest_author":"https://pith.science/pith/57LOPKAWNY22PWISATNGNPW7VX/action/author_attestation","sign_citation":"https://pith.science/pith/57LOPKAWNY22PWISATNGNPW7VX/action/citation_signature","submit_replication":"https://pith.science/pith/57LOPKAWNY22PWISATNGNPW7VX/action/replication_record"}},"created_at":"2026-07-05T02:05:51.222930+00:00","updated_at":"2026-07-05T02:05:51.222930+00:00"}