{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:XEOEAH7JC3BATI2O6FRQTXRXGW","short_pith_number":"pith:XEOEAH7J","schema_version":"1.0","canonical_sha256":"b91c401fe916c209a34ef16309de373595524b107cdfba6bb0dab9eb3e17b025","source":{"kind":"arxiv","id":"2506.14295","version":1},"attestation_state":"computed","paper":{"title":"The Impact of Generative AI on Social Media: An Experimental Study","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Anders Giovanni M{\\o}ller, Daniel M. Romero, David Jurgens, Luca Maria Aiello","submitted_at":"2025-06-17T08:13:01Z","abstract_excerpt":"Generative Artificial Intelligence (AI) tools are increasingly deployed across social media platforms, yet their implications for user behavior and experience remain understudied, particularly regarding two critical dimensions: (1) how AI tools affect the behaviors of content producers in a social media context, and (2) how content generated with AI assistance is perceived by users. To fill this gap, we conduct a controlled experiment with a representative sample of 680 U.S. participants in a realistic social media environment. The participants are randomly assigned to small discussion groups,"},"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":"2506.14295","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2025-06-17T08:13:01Z","cross_cats_sorted":[],"title_canon_sha256":"fd6c6c012d97c04fe3b36cfb9ee3539da9bb9d6a4c19b44510b9f1d0e589b22c","abstract_canon_sha256":"bb923cb4d764b7a4abe4e9781b18f5a68227be29b46ac456e3a7ef38e9b38f91"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:22:52.817369Z","signature_b64":"rTMeMj3BYvnpXuhvu0/CG6UA1tuhSB+nqu0mOlhi/QR7DeOReGDyEZirU2tOv0MHfa3pQMsNdm+MBEqcxMvJBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b91c401fe916c209a34ef16309de373595524b107cdfba6bb0dab9eb3e17b025","last_reissued_at":"2026-07-05T11:22:52.816828Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:22:52.816828Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The Impact of Generative AI on Social Media: An Experimental Study","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Anders Giovanni M{\\o}ller, Daniel M. Romero, David Jurgens, Luca Maria Aiello","submitted_at":"2025-06-17T08:13:01Z","abstract_excerpt":"Generative Artificial Intelligence (AI) tools are increasingly deployed across social media platforms, yet their implications for user behavior and experience remain understudied, particularly regarding two critical dimensions: (1) how AI tools affect the behaviors of content producers in a social media context, and (2) how content generated with AI assistance is perceived by users. To fill this gap, we conduct a controlled experiment with a representative sample of 680 U.S. participants in a realistic social media environment. The participants are randomly assigned to small discussion groups,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.14295","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/2506.14295/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":"2506.14295","created_at":"2026-07-05T11:22:52.816889+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.14295v1","created_at":"2026-07-05T11:22:52.816889+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.14295","created_at":"2026-07-05T11:22:52.816889+00:00"},{"alias_kind":"pith_short_12","alias_value":"XEOEAH7JC3BA","created_at":"2026-07-05T11:22:52.816889+00:00"},{"alias_kind":"pith_short_16","alias_value":"XEOEAH7JC3BATI2O","created_at":"2026-07-05T11:22:52.816889+00:00"},{"alias_kind":"pith_short_8","alias_value":"XEOEAH7J","created_at":"2026-07-05T11:22:52.816889+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.00657","citing_title":"Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity","ref_index":11,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XEOEAH7JC3BATI2O6FRQTXRXGW","json":"https://pith.science/pith/XEOEAH7JC3BATI2O6FRQTXRXGW.json","graph_json":"https://pith.science/api/pith-number/XEOEAH7JC3BATI2O6FRQTXRXGW/graph.json","events_json":"https://pith.science/api/pith-number/XEOEAH7JC3BATI2O6FRQTXRXGW/events.json","paper":"https://pith.science/paper/XEOEAH7J"},"agent_actions":{"view_html":"https://pith.science/pith/XEOEAH7JC3BATI2O6FRQTXRXGW","download_json":"https://pith.science/pith/XEOEAH7JC3BATI2O6FRQTXRXGW.json","view_paper":"https://pith.science/paper/XEOEAH7J","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.14295&json=true","fetch_graph":"https://pith.science/api/pith-number/XEOEAH7JC3BATI2O6FRQTXRXGW/graph.json","fetch_events":"https://pith.science/api/pith-number/XEOEAH7JC3BATI2O6FRQTXRXGW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XEOEAH7JC3BATI2O6FRQTXRXGW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XEOEAH7JC3BATI2O6FRQTXRXGW/action/storage_attestation","attest_author":"https://pith.science/pith/XEOEAH7JC3BATI2O6FRQTXRXGW/action/author_attestation","sign_citation":"https://pith.science/pith/XEOEAH7JC3BATI2O6FRQTXRXGW/action/citation_signature","submit_replication":"https://pith.science/pith/XEOEAH7JC3BATI2O6FRQTXRXGW/action/replication_record"}},"created_at":"2026-07-05T11:22:52.816889+00:00","updated_at":"2026-07-05T11:22:52.816889+00:00"}