{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:OLRQD3RNVZEMFSZZDKMFEYINVC","short_pith_number":"pith:OLRQD3RN","schema_version":"1.0","canonical_sha256":"72e301ee2dae48c2cb391a9852610da8be02bf4a26be027bb8b7c671e1c1eef9","source":{"kind":"arxiv","id":"1605.05401","version":1},"attestation_state":"computed","paper":{"title":"Pricing the Woman Card: Gender Politics between Hillary Clinton and Donald Trump","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Jiebo Luo, Richard Niemi, Xiyang Zhang, Yang Feng, Yuncheng Li, Yu Wang","submitted_at":"2016-05-18T00:00:44Z","abstract_excerpt":"In this paper, we propose a data-driven method to measure the impact of the 'woman card' exchange between Hillary Clinton and Donald Trump. Building from a unique dataset of the two candidates' Twitter followers, we first examine the transition dynamics of the two candidates' Twitter followers one week before the exchange and one week after. Then we train a convolutional neural network to classify the gender of the followers and unfollowers, and study how women in particular are reacting to the 'woman card' exchange. Our study suggests that the 'woman card' comment has made women more likely t"},"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":"1605.05401","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2016-05-18T00:00:44Z","cross_cats_sorted":[],"title_canon_sha256":"cd60104458792a55eaa4c899a61794ee4c308c78d326e2310028bf71085dc130","abstract_canon_sha256":"cfdf27f427e0fb822ac06009d5dadb3684d1f2a9768d30490e7de9a1b8a16fbd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:14:35.108542Z","signature_b64":"dvs5lIBipoQm0FztwWb0RXPsKRXlG9C89BgamT7ZB9KOfO0nEzX7InQldv+HEpQPtHwdiNCcqwUPvMn4JcCsAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"72e301ee2dae48c2cb391a9852610da8be02bf4a26be027bb8b7c671e1c1eef9","last_reissued_at":"2026-05-18T01:14:35.107852Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:14:35.107852Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Pricing the Woman Card: Gender Politics between Hillary Clinton and Donald Trump","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Jiebo Luo, Richard Niemi, Xiyang Zhang, Yang Feng, Yuncheng Li, Yu Wang","submitted_at":"2016-05-18T00:00:44Z","abstract_excerpt":"In this paper, we propose a data-driven method to measure the impact of the 'woman card' exchange between Hillary Clinton and Donald Trump. Building from a unique dataset of the two candidates' Twitter followers, we first examine the transition dynamics of the two candidates' Twitter followers one week before the exchange and one week after. Then we train a convolutional neural network to classify the gender of the followers and unfollowers, and study how women in particular are reacting to the 'woman card' exchange. Our study suggests that the 'woman card' comment has made women more likely t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.05401","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1605.05401","created_at":"2026-05-18T01:14:35.107952+00:00"},{"alias_kind":"arxiv_version","alias_value":"1605.05401v1","created_at":"2026-05-18T01:14:35.107952+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.05401","created_at":"2026-05-18T01:14:35.107952+00:00"},{"alias_kind":"pith_short_12","alias_value":"OLRQD3RNVZEM","created_at":"2026-05-18T12:30:36.002864+00:00"},{"alias_kind":"pith_short_16","alias_value":"OLRQD3RNVZEMFSZZ","created_at":"2026-05-18T12:30:36.002864+00:00"},{"alias_kind":"pith_short_8","alias_value":"OLRQD3RN","created_at":"2026-05-18T12:30:36.002864+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/OLRQD3RNVZEMFSZZDKMFEYINVC","json":"https://pith.science/pith/OLRQD3RNVZEMFSZZDKMFEYINVC.json","graph_json":"https://pith.science/api/pith-number/OLRQD3RNVZEMFSZZDKMFEYINVC/graph.json","events_json":"https://pith.science/api/pith-number/OLRQD3RNVZEMFSZZDKMFEYINVC/events.json","paper":"https://pith.science/paper/OLRQD3RN"},"agent_actions":{"view_html":"https://pith.science/pith/OLRQD3RNVZEMFSZZDKMFEYINVC","download_json":"https://pith.science/pith/OLRQD3RNVZEMFSZZDKMFEYINVC.json","view_paper":"https://pith.science/paper/OLRQD3RN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1605.05401&json=true","fetch_graph":"https://pith.science/api/pith-number/OLRQD3RNVZEMFSZZDKMFEYINVC/graph.json","fetch_events":"https://pith.science/api/pith-number/OLRQD3RNVZEMFSZZDKMFEYINVC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OLRQD3RNVZEMFSZZDKMFEYINVC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OLRQD3RNVZEMFSZZDKMFEYINVC/action/storage_attestation","attest_author":"https://pith.science/pith/OLRQD3RNVZEMFSZZDKMFEYINVC/action/author_attestation","sign_citation":"https://pith.science/pith/OLRQD3RNVZEMFSZZDKMFEYINVC/action/citation_signature","submit_replication":"https://pith.science/pith/OLRQD3RNVZEMFSZZDKMFEYINVC/action/replication_record"}},"created_at":"2026-05-18T01:14:35.107952+00:00","updated_at":"2026-05-18T01:14:35.107952+00:00"}