{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:IBRIB5GUHZSELIASWWF5D3WETN","short_pith_number":"pith:IBRIB5GU","schema_version":"1.0","canonical_sha256":"406280f4d43e6445a012b58bd1eec49b4d13c622ae99dc050b21ba4461eab179","source":{"kind":"arxiv","id":"2410.17390","version":4},"attestation_state":"computed","paper":{"title":"Revealing The Secret Power: How Algorithms Can Influence Content Visibility on Twitter/X","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Alessandro Galeazzi, Emiliano De Cristofaro, Gianluca Stringhini, Mauro Conti, Pujan Paudel","submitted_at":"2024-10-22T19:58:56Z","abstract_excerpt":"In recent years, the opaque design and the limited public understanding of social networks' recommendation algorithms have raised concerns about potential manipulation of information exposure. Reducing content visibility, aka shadow banning, may help limit harmful content; however, it can also be used to suppress dissenting voices. This prompts the need for greater transparency and a better understanding of this practice.\n  In this paper, we investigate the presence of visibility alterations through a large-scale quantitative analysis of two Twitter/X datasets comprising over 40 million tweets"},"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":"2410.17390","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2024-10-22T19:58:56Z","cross_cats_sorted":[],"title_canon_sha256":"053b3c0984d014ffc08891d72bc3b43b0a7905983bc6fc3c1faa930961f6c14f","abstract_canon_sha256":"f339a5f337902be0544f7e1f8e9652f4ec4cc5d1b4a920707be9f1663b9070a4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:07:01.360164Z","signature_b64":"J+m0cBVinDQXB18uFJ76SkY+wOY2x2gFsu7mSKItMkWrOKvI4GEUwnd9kMlFrIA95lQoyu9eN0+5a4ZqtMXRBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"406280f4d43e6445a012b58bd1eec49b4d13c622ae99dc050b21ba4461eab179","last_reissued_at":"2026-07-05T12:07:01.359667Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:07:01.359667Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Revealing The Secret Power: How Algorithms Can Influence Content Visibility on Twitter/X","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Alessandro Galeazzi, Emiliano De Cristofaro, Gianluca Stringhini, Mauro Conti, Pujan Paudel","submitted_at":"2024-10-22T19:58:56Z","abstract_excerpt":"In recent years, the opaque design and the limited public understanding of social networks' recommendation algorithms have raised concerns about potential manipulation of information exposure. Reducing content visibility, aka shadow banning, may help limit harmful content; however, it can also be used to suppress dissenting voices. This prompts the need for greater transparency and a better understanding of this practice.\n  In this paper, we investigate the presence of visibility alterations through a large-scale quantitative analysis of two Twitter/X datasets comprising over 40 million tweets"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.17390","kind":"arxiv","version":4},"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/2410.17390/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":"2410.17390","created_at":"2026-07-05T12:07:01.359727+00:00"},{"alias_kind":"arxiv_version","alias_value":"2410.17390v4","created_at":"2026-07-05T12:07:01.359727+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.17390","created_at":"2026-07-05T12:07:01.359727+00:00"},{"alias_kind":"pith_short_12","alias_value":"IBRIB5GUHZSE","created_at":"2026-07-05T12:07:01.359727+00:00"},{"alias_kind":"pith_short_16","alias_value":"IBRIB5GUHZSELIAS","created_at":"2026-07-05T12:07:01.359727+00:00"},{"alias_kind":"pith_short_8","alias_value":"IBRIB5GU","created_at":"2026-07-05T12:07:01.359727+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2505.01122","citing_title":"The Great Data Standoff: Researchers vs. Platforms Under the Digital Services Act","ref_index":2025,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/IBRIB5GUHZSELIASWWF5D3WETN","json":"https://pith.science/pith/IBRIB5GUHZSELIASWWF5D3WETN.json","graph_json":"https://pith.science/api/pith-number/IBRIB5GUHZSELIASWWF5D3WETN/graph.json","events_json":"https://pith.science/api/pith-number/IBRIB5GUHZSELIASWWF5D3WETN/events.json","paper":"https://pith.science/paper/IBRIB5GU"},"agent_actions":{"view_html":"https://pith.science/pith/IBRIB5GUHZSELIASWWF5D3WETN","download_json":"https://pith.science/pith/IBRIB5GUHZSELIASWWF5D3WETN.json","view_paper":"https://pith.science/paper/IBRIB5GU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2410.17390&json=true","fetch_graph":"https://pith.science/api/pith-number/IBRIB5GUHZSELIASWWF5D3WETN/graph.json","fetch_events":"https://pith.science/api/pith-number/IBRIB5GUHZSELIASWWF5D3WETN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IBRIB5GUHZSELIASWWF5D3WETN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IBRIB5GUHZSELIASWWF5D3WETN/action/storage_attestation","attest_author":"https://pith.science/pith/IBRIB5GUHZSELIASWWF5D3WETN/action/author_attestation","sign_citation":"https://pith.science/pith/IBRIB5GUHZSELIASWWF5D3WETN/action/citation_signature","submit_replication":"https://pith.science/pith/IBRIB5GUHZSELIASWWF5D3WETN/action/replication_record"}},"created_at":"2026-07-05T12:07:01.359727+00:00","updated_at":"2026-07-05T12:07:01.359727+00:00"}