{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:FYGMMNYM4IABC2575PEOWG556Q","short_pith_number":"pith:FYGMMNYM","schema_version":"1.0","canonical_sha256":"2e0cc6370ce200116bbfebc8eb1bbdf431356f9c9eecf46c0bfa1419b26545e5","source":{"kind":"arxiv","id":"2007.13968","version":1},"attestation_state":"computed","paper":{"title":"YNU-HPCC at SemEval-2020 Task 8: Using a Parallel-Channel Model for Memotion Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jin Wang, Li Yuan, Xuejie Zhang","submitted_at":"2020-07-28T03:20:31Z","abstract_excerpt":"In recent years, the growing ubiquity of Internet memes on social media platforms, such as Facebook, Instagram, and Twitter, has become a topic of immense interest. However, the classification and recognition of memes is much more complicated than that of social text since it involves visual cues and language understanding. To address this issue, this paper proposed a parallel-channel model to process the textual and visual information in memes and then analyze the sentiment polarity of memes. In the shared task of identifying and categorizing memes, we preprocess the dataset according to the "},"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":"2007.13968","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-07-28T03:20:31Z","cross_cats_sorted":[],"title_canon_sha256":"536f867922d29d96e65f74bb2eeb9a753b6a1cac9f9f3610834a2cf9646565f4","abstract_canon_sha256":"136104eb004a057f7a3472d9fe59a160c09ce0c564f7203ce1297596e211f0ba"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:22:54.085603Z","signature_b64":"EFeNjxPBKwpg3ns1fu8gkWq0tNtDTWi0jFQrwSd5uegzDl0ycSvcHyh2Todp1v6luA3Sys9P+RarfyNphutOAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2e0cc6370ce200116bbfebc8eb1bbdf431356f9c9eecf46c0bfa1419b26545e5","last_reissued_at":"2026-07-05T01:22:54.085219Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:22:54.085219Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"YNU-HPCC at SemEval-2020 Task 8: Using a Parallel-Channel Model for Memotion Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jin Wang, Li Yuan, Xuejie Zhang","submitted_at":"2020-07-28T03:20:31Z","abstract_excerpt":"In recent years, the growing ubiquity of Internet memes on social media platforms, such as Facebook, Instagram, and Twitter, has become a topic of immense interest. However, the classification and recognition of memes is much more complicated than that of social text since it involves visual cues and language understanding. To address this issue, this paper proposed a parallel-channel model to process the textual and visual information in memes and then analyze the sentiment polarity of memes. In the shared task of identifying and categorizing memes, we preprocess the dataset according to the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.13968","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/2007.13968/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":"2007.13968","created_at":"2026-07-05T01:22:54.085274+00:00"},{"alias_kind":"arxiv_version","alias_value":"2007.13968v1","created_at":"2026-07-05T01:22:54.085274+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.13968","created_at":"2026-07-05T01:22:54.085274+00:00"},{"alias_kind":"pith_short_12","alias_value":"FYGMMNYM4IAB","created_at":"2026-07-05T01:22:54.085274+00:00"},{"alias_kind":"pith_short_16","alias_value":"FYGMMNYM4IABC257","created_at":"2026-07-05T01:22:54.085274+00:00"},{"alias_kind":"pith_short_8","alias_value":"FYGMMNYM","created_at":"2026-07-05T01:22:54.085274+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/FYGMMNYM4IABC2575PEOWG556Q","json":"https://pith.science/pith/FYGMMNYM4IABC2575PEOWG556Q.json","graph_json":"https://pith.science/api/pith-number/FYGMMNYM4IABC2575PEOWG556Q/graph.json","events_json":"https://pith.science/api/pith-number/FYGMMNYM4IABC2575PEOWG556Q/events.json","paper":"https://pith.science/paper/FYGMMNYM"},"agent_actions":{"view_html":"https://pith.science/pith/FYGMMNYM4IABC2575PEOWG556Q","download_json":"https://pith.science/pith/FYGMMNYM4IABC2575PEOWG556Q.json","view_paper":"https://pith.science/paper/FYGMMNYM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2007.13968&json=true","fetch_graph":"https://pith.science/api/pith-number/FYGMMNYM4IABC2575PEOWG556Q/graph.json","fetch_events":"https://pith.science/api/pith-number/FYGMMNYM4IABC2575PEOWG556Q/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FYGMMNYM4IABC2575PEOWG556Q/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FYGMMNYM4IABC2575PEOWG556Q/action/storage_attestation","attest_author":"https://pith.science/pith/FYGMMNYM4IABC2575PEOWG556Q/action/author_attestation","sign_citation":"https://pith.science/pith/FYGMMNYM4IABC2575PEOWG556Q/action/citation_signature","submit_replication":"https://pith.science/pith/FYGMMNYM4IABC2575PEOWG556Q/action/replication_record"}},"created_at":"2026-07-05T01:22:54.085274+00:00","updated_at":"2026-07-05T01:22:54.085274+00:00"}