{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:Y2MRQC2H46GQUHWJCX4GPCSEKT","short_pith_number":"pith:Y2MRQC2H","schema_version":"1.0","canonical_sha256":"c699180b47e78d0a1ec915f8678a4454c648d8dbb37edd3231cc5d0529336850","source":{"kind":"arxiv","id":"2403.12356","version":1},"attestation_state":"computed","paper":{"title":"MoodSmith: Enabling Mood-Consistent Multimedia for AI-Generated Advocacy Campaigns","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Lydia Chilton, Samia Menon, Sitong Wang","submitted_at":"2024-03-19T01:58:59Z","abstract_excerpt":"Emotion is vital to information and message processing, playing a key role in attitude formation. Consequently, creating a mood that evokes an emotional response is essential to any compelling piece of outreach communication. Many nonprofits and charities, despite having established messages, face challenges in creating advocacy campaign videos for social media. It requires significant creative and cognitive efforts to ensure that videos achieve the desired mood across multiple dimensions: script, visuals, and audio. We introduce MoodSmith, an AI-powered system that helps users explore mood po"},"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":"2403.12356","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2024-03-19T01:58:59Z","cross_cats_sorted":[],"title_canon_sha256":"bcc18f5930b00174496c09a4803ca67908ddc9b36032180a95885c146ac4c84c","abstract_canon_sha256":"4c89a28a5b87c3326bddceb75504ef20e66916c014562e5dadb7cc6e69a6aabc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:57:59.968224Z","signature_b64":"pcaaIr3Ejd7M9ZQWcQf75IbrLopGRF4wv0rN9B6IxjHMXv/U11M/yg9HHlBNVQvN7nm31GuTxm0W+XTh8hVyCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c699180b47e78d0a1ec915f8678a4454c648d8dbb37edd3231cc5d0529336850","last_reissued_at":"2026-07-05T07:57:59.967800Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:57:59.967800Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MoodSmith: Enabling Mood-Consistent Multimedia for AI-Generated Advocacy Campaigns","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Lydia Chilton, Samia Menon, Sitong Wang","submitted_at":"2024-03-19T01:58:59Z","abstract_excerpt":"Emotion is vital to information and message processing, playing a key role in attitude formation. Consequently, creating a mood that evokes an emotional response is essential to any compelling piece of outreach communication. Many nonprofits and charities, despite having established messages, face challenges in creating advocacy campaign videos for social media. It requires significant creative and cognitive efforts to ensure that videos achieve the desired mood across multiple dimensions: script, visuals, and audio. We introduce MoodSmith, an AI-powered system that helps users explore mood po"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.12356","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/2403.12356/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":"2403.12356","created_at":"2026-07-05T07:57:59.967870+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.12356v1","created_at":"2026-07-05T07:57:59.967870+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.12356","created_at":"2026-07-05T07:57:59.967870+00:00"},{"alias_kind":"pith_short_12","alias_value":"Y2MRQC2H46GQ","created_at":"2026-07-05T07:57:59.967870+00:00"},{"alias_kind":"pith_short_16","alias_value":"Y2MRQC2H46GQUHWJ","created_at":"2026-07-05T07:57:59.967870+00:00"},{"alias_kind":"pith_short_8","alias_value":"Y2MRQC2H","created_at":"2026-07-05T07:57:59.967870+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2504.11795","citing_title":"Schemex: Discovering Structural Abstractions from Examples","ref_index":39,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/Y2MRQC2H46GQUHWJCX4GPCSEKT","json":"https://pith.science/pith/Y2MRQC2H46GQUHWJCX4GPCSEKT.json","graph_json":"https://pith.science/api/pith-number/Y2MRQC2H46GQUHWJCX4GPCSEKT/graph.json","events_json":"https://pith.science/api/pith-number/Y2MRQC2H46GQUHWJCX4GPCSEKT/events.json","paper":"https://pith.science/paper/Y2MRQC2H"},"agent_actions":{"view_html":"https://pith.science/pith/Y2MRQC2H46GQUHWJCX4GPCSEKT","download_json":"https://pith.science/pith/Y2MRQC2H46GQUHWJCX4GPCSEKT.json","view_paper":"https://pith.science/paper/Y2MRQC2H","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.12356&json=true","fetch_graph":"https://pith.science/api/pith-number/Y2MRQC2H46GQUHWJCX4GPCSEKT/graph.json","fetch_events":"https://pith.science/api/pith-number/Y2MRQC2H46GQUHWJCX4GPCSEKT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Y2MRQC2H46GQUHWJCX4GPCSEKT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Y2MRQC2H46GQUHWJCX4GPCSEKT/action/storage_attestation","attest_author":"https://pith.science/pith/Y2MRQC2H46GQUHWJCX4GPCSEKT/action/author_attestation","sign_citation":"https://pith.science/pith/Y2MRQC2H46GQUHWJCX4GPCSEKT/action/citation_signature","submit_replication":"https://pith.science/pith/Y2MRQC2H46GQUHWJCX4GPCSEKT/action/replication_record"}},"created_at":"2026-07-05T07:57:59.967870+00:00","updated_at":"2026-07-05T07:57:59.967870+00:00"}