{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:GE773KMT5YVUBJ4QKMJ5T67CDY","short_pith_number":"pith:GE773KMT","schema_version":"1.0","canonical_sha256":"313ffda993ee2b40a7905313d9fbe21e20ef9bda9d974d32d0af0eac477df828","source":{"kind":"arxiv","id":"2402.02056","version":1},"attestation_state":"computed","paper":{"title":"AnthroScore: A Computational Linguistic Measure of Anthropomorphism","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CY"],"primary_cat":"cs.CL","authors_text":"Dan Jurafsky, Kristina Gligoric, Myra Cheng, Tiziano Piccardi","submitted_at":"2024-02-03T06:36:11Z","abstract_excerpt":"Anthropomorphism, or the attribution of human-like characteristics to non-human entities, has shaped conversations about the impacts and possibilities of technology. We present AnthroScore, an automatic metric of implicit anthropomorphism in language. We use a masked language model to quantify how non-human entities are implicitly framed as human by the surrounding context. We show that AnthroScore corresponds with human judgments of anthropomorphism and dimensions of anthropomorphism described in social science literature. Motivated by concerns of misleading anthropomorphism in computer scien"},"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":"2402.02056","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-03T06:36:11Z","cross_cats_sorted":["cs.AI","cs.CY"],"title_canon_sha256":"3b99ecff314ac746384f9378a35885cb041bbda749b26b00c41af11cbd455142","abstract_canon_sha256":"aef966d07cc28d79ca218c18a07bdded3a623e64d891878df2cb5562391e0de5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:41:10.293566Z","signature_b64":"K4zqr9EQfuTd913PgJOA5ejxwptsoAPXsQcvRN5qpSGjhzEp2Wz1SvhZgrgOQmE4IIJIUSpiGelw9Fd1xSHgDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"313ffda993ee2b40a7905313d9fbe21e20ef9bda9d974d32d0af0eac477df828","last_reissued_at":"2026-07-05T07:41:10.293081Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:41:10.293081Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"AnthroScore: A Computational Linguistic Measure of Anthropomorphism","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CY"],"primary_cat":"cs.CL","authors_text":"Dan Jurafsky, Kristina Gligoric, Myra Cheng, Tiziano Piccardi","submitted_at":"2024-02-03T06:36:11Z","abstract_excerpt":"Anthropomorphism, or the attribution of human-like characteristics to non-human entities, has shaped conversations about the impacts and possibilities of technology. We present AnthroScore, an automatic metric of implicit anthropomorphism in language. We use a masked language model to quantify how non-human entities are implicitly framed as human by the surrounding context. We show that AnthroScore corresponds with human judgments of anthropomorphism and dimensions of anthropomorphism described in social science literature. Motivated by concerns of misleading anthropomorphism in computer scien"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.02056","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/2402.02056/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":"2402.02056","created_at":"2026-07-05T07:41:10.293138+00:00"},{"alias_kind":"arxiv_version","alias_value":"2402.02056v1","created_at":"2026-07-05T07:41:10.293138+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.02056","created_at":"2026-07-05T07:41:10.293138+00:00"},{"alias_kind":"pith_short_12","alias_value":"GE773KMT5YVU","created_at":"2026-07-05T07:41:10.293138+00:00"},{"alias_kind":"pith_short_16","alias_value":"GE773KMT5YVUBJ4Q","created_at":"2026-07-05T07:41:10.293138+00:00"},{"alias_kind":"pith_short_8","alias_value":"GE773KMT","created_at":"2026-07-05T07:41:10.293138+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.30942","citing_title":"Anthropomorphism in AI Companion Communities: Age, Gender, and Emotional Correlates","ref_index":34,"is_internal_anchor":false},{"citing_arxiv_id":"2510.03761","citing_title":"You Have Been LaTeXpOsEd: A Systematic Analysis of Information Leakage in Preprint Archives Using Large Language Models","ref_index":8,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/GE773KMT5YVUBJ4QKMJ5T67CDY","json":"https://pith.science/pith/GE773KMT5YVUBJ4QKMJ5T67CDY.json","graph_json":"https://pith.science/api/pith-number/GE773KMT5YVUBJ4QKMJ5T67CDY/graph.json","events_json":"https://pith.science/api/pith-number/GE773KMT5YVUBJ4QKMJ5T67CDY/events.json","paper":"https://pith.science/paper/GE773KMT"},"agent_actions":{"view_html":"https://pith.science/pith/GE773KMT5YVUBJ4QKMJ5T67CDY","download_json":"https://pith.science/pith/GE773KMT5YVUBJ4QKMJ5T67CDY.json","view_paper":"https://pith.science/paper/GE773KMT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2402.02056&json=true","fetch_graph":"https://pith.science/api/pith-number/GE773KMT5YVUBJ4QKMJ5T67CDY/graph.json","fetch_events":"https://pith.science/api/pith-number/GE773KMT5YVUBJ4QKMJ5T67CDY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GE773KMT5YVUBJ4QKMJ5T67CDY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GE773KMT5YVUBJ4QKMJ5T67CDY/action/storage_attestation","attest_author":"https://pith.science/pith/GE773KMT5YVUBJ4QKMJ5T67CDY/action/author_attestation","sign_citation":"https://pith.science/pith/GE773KMT5YVUBJ4QKMJ5T67CDY/action/citation_signature","submit_replication":"https://pith.science/pith/GE773KMT5YVUBJ4QKMJ5T67CDY/action/replication_record"}},"created_at":"2026-07-05T07:41:10.293138+00:00","updated_at":"2026-07-05T07:41:10.293138+00:00"}