{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:QNI5A5GVM44ZINCUIZ36NPO6HX","short_pith_number":"pith:QNI5A5GV","schema_version":"1.0","canonical_sha256":"8351d074d567399434544677e6bdde3dcd0ee1eb71334cd6ffa36f6bc346278f","source":{"kind":"arxiv","id":"1309.5942","version":1},"attestation_state":"computed","paper":{"title":"Colourful Language: Measuring Word-Colour Associations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Saif Mohammad","submitted_at":"2013-09-20T21:10:56Z","abstract_excerpt":"Since many real-world concepts are associated with colour, for example danger with red, linguistic information is often complimented with the use of appropriate colours in information visualization and product marketing. Yet, there is no comprehensive resource that captures concept-colour associations. We present a method to create a large word-colour association lexicon by crowdsourcing. We focus especially on abstract concepts and emotions to show that even though they cannot be physically visualized, they too tend to have strong colour associations. Finally, we show how word-colour associat"},"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":"1309.5942","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2013-09-20T21:10:56Z","cross_cats_sorted":[],"title_canon_sha256":"af3a0f0a84e1e63180fec2a951a0d6301ac6e94d119616512a6980ca924345cf","abstract_canon_sha256":"3b1b093fc3d797cf6ed388f410762ae4cd1d6ac83501c95d6100234b5e688fe4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:12:32.229007Z","signature_b64":"6UnVQ6Oo0VW5isibctWUaOV4hd7Vx3XJ1rpn5wEFpiLX/xHq6Z8Fv1iFBVhXgCDVEex++d1I5RgVcvzN8zz5Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8351d074d567399434544677e6bdde3dcd0ee1eb71334cd6ffa36f6bc346278f","last_reissued_at":"2026-05-18T03:12:32.228401Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:12:32.228401Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Colourful Language: Measuring Word-Colour Associations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Saif Mohammad","submitted_at":"2013-09-20T21:10:56Z","abstract_excerpt":"Since many real-world concepts are associated with colour, for example danger with red, linguistic information is often complimented with the use of appropriate colours in information visualization and product marketing. Yet, there is no comprehensive resource that captures concept-colour associations. We present a method to create a large word-colour association lexicon by crowdsourcing. We focus especially on abstract concepts and emotions to show that even though they cannot be physically visualized, they too tend to have strong colour associations. Finally, we show how word-colour associat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1309.5942","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":"1309.5942","created_at":"2026-05-18T03:12:32.228519+00:00"},{"alias_kind":"arxiv_version","alias_value":"1309.5942v1","created_at":"2026-05-18T03:12:32.228519+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1309.5942","created_at":"2026-05-18T03:12:32.228519+00:00"},{"alias_kind":"pith_short_12","alias_value":"QNI5A5GVM44Z","created_at":"2026-05-18T12:27:57.521954+00:00"},{"alias_kind":"pith_short_16","alias_value":"QNI5A5GVM44ZINCU","created_at":"2026-05-18T12:27:57.521954+00:00"},{"alias_kind":"pith_short_8","alias_value":"QNI5A5GV","created_at":"2026-05-18T12:27:57.521954+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2607.02455","citing_title":"When Do LLM Personas Support Visualization Design? A Cross-Model Study of Color Assignment and Chart Choice","ref_index":15,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QNI5A5GVM44ZINCUIZ36NPO6HX","json":"https://pith.science/pith/QNI5A5GVM44ZINCUIZ36NPO6HX.json","graph_json":"https://pith.science/api/pith-number/QNI5A5GVM44ZINCUIZ36NPO6HX/graph.json","events_json":"https://pith.science/api/pith-number/QNI5A5GVM44ZINCUIZ36NPO6HX/events.json","paper":"https://pith.science/paper/QNI5A5GV"},"agent_actions":{"view_html":"https://pith.science/pith/QNI5A5GVM44ZINCUIZ36NPO6HX","download_json":"https://pith.science/pith/QNI5A5GVM44ZINCUIZ36NPO6HX.json","view_paper":"https://pith.science/paper/QNI5A5GV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1309.5942&json=true","fetch_graph":"https://pith.science/api/pith-number/QNI5A5GVM44ZINCUIZ36NPO6HX/graph.json","fetch_events":"https://pith.science/api/pith-number/QNI5A5GVM44ZINCUIZ36NPO6HX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QNI5A5GVM44ZINCUIZ36NPO6HX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QNI5A5GVM44ZINCUIZ36NPO6HX/action/storage_attestation","attest_author":"https://pith.science/pith/QNI5A5GVM44ZINCUIZ36NPO6HX/action/author_attestation","sign_citation":"https://pith.science/pith/QNI5A5GVM44ZINCUIZ36NPO6HX/action/citation_signature","submit_replication":"https://pith.science/pith/QNI5A5GVM44ZINCUIZ36NPO6HX/action/replication_record"}},"created_at":"2026-05-18T03:12:32.228519+00:00","updated_at":"2026-05-18T03:12:32.228519+00:00"}