{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:PXFZYWCO32WTE7WOGTGUTY4TRZ","short_pith_number":"pith:PXFZYWCO","schema_version":"1.0","canonical_sha256":"7dcb9c584edead327ece34cd49e3938e5056160d13808bcd89aff4a03f9eae55","source":{"kind":"arxiv","id":"1707.06806","version":1},"attestation_state":"computed","paper":{"title":"Shallow reading with Deep Learning: Predicting popularity of online content using only its title","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Krzysztof Marasek, Krzysztof Wolk, Przemyslaw Rokita, Tomasz Trzcinski, Wociech Stokowiec","submitted_at":"2017-07-21T09:02:55Z","abstract_excerpt":"With the ever decreasing attention span of contemporary Internet users, the title of online content (such as a news article or video) can be a major factor in determining its popularity. To take advantage of this phenomenon, we propose a new method based on a bidirectional Long Short-Term Memory (LSTM) neural network designed to predict the popularity of online content using only its title. We evaluate the proposed architecture on two distinct datasets of news articles and news videos distributed in social media that contain over 40,000 samples in total. On those datasets, our approach improve"},"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":"1707.06806","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-07-21T09:02:55Z","cross_cats_sorted":[],"title_canon_sha256":"c517d628c47aa3f774974da3f7c5e94f561b654d4366e4188a108a605e2f767e","abstract_canon_sha256":"b59a492c450d6b45583853ffc8e0cda077a9c69d74ba5ab8ae5157de3da8ced5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:51.568871Z","signature_b64":"zB0kjz8gQ/9pkQECkMUc7eNzd/aOLvUc1CbgHnVEnmJ77XmKaPHJ34i33hHe7hy9gWh4eZQgCbgguUMBRK6MAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7dcb9c584edead327ece34cd49e3938e5056160d13808bcd89aff4a03f9eae55","last_reissued_at":"2026-05-18T00:39:51.567546Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:51.567546Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Shallow reading with Deep Learning: Predicting popularity of online content using only its title","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Krzysztof Marasek, Krzysztof Wolk, Przemyslaw Rokita, Tomasz Trzcinski, Wociech Stokowiec","submitted_at":"2017-07-21T09:02:55Z","abstract_excerpt":"With the ever decreasing attention span of contemporary Internet users, the title of online content (such as a news article or video) can be a major factor in determining its popularity. To take advantage of this phenomenon, we propose a new method based on a bidirectional Long Short-Term Memory (LSTM) neural network designed to predict the popularity of online content using only its title. We evaluate the proposed architecture on two distinct datasets of news articles and news videos distributed in social media that contain over 40,000 samples in total. On those datasets, our approach improve"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.06806","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":"1707.06806","created_at":"2026-05-18T00:39:51.567652+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.06806v1","created_at":"2026-05-18T00:39:51.567652+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.06806","created_at":"2026-05-18T00:39:51.567652+00:00"},{"alias_kind":"pith_short_12","alias_value":"PXFZYWCO32WT","created_at":"2026-05-18T12:31:37.085036+00:00"},{"alias_kind":"pith_short_16","alias_value":"PXFZYWCO32WTE7WO","created_at":"2026-05-18T12:31:37.085036+00:00"},{"alias_kind":"pith_short_8","alias_value":"PXFZYWCO","created_at":"2026-05-18T12:31:37.085036+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PXFZYWCO32WTE7WOGTGUTY4TRZ","json":"https://pith.science/pith/PXFZYWCO32WTE7WOGTGUTY4TRZ.json","graph_json":"https://pith.science/api/pith-number/PXFZYWCO32WTE7WOGTGUTY4TRZ/graph.json","events_json":"https://pith.science/api/pith-number/PXFZYWCO32WTE7WOGTGUTY4TRZ/events.json","paper":"https://pith.science/paper/PXFZYWCO"},"agent_actions":{"view_html":"https://pith.science/pith/PXFZYWCO32WTE7WOGTGUTY4TRZ","download_json":"https://pith.science/pith/PXFZYWCO32WTE7WOGTGUTY4TRZ.json","view_paper":"https://pith.science/paper/PXFZYWCO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.06806&json=true","fetch_graph":"https://pith.science/api/pith-number/PXFZYWCO32WTE7WOGTGUTY4TRZ/graph.json","fetch_events":"https://pith.science/api/pith-number/PXFZYWCO32WTE7WOGTGUTY4TRZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PXFZYWCO32WTE7WOGTGUTY4TRZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PXFZYWCO32WTE7WOGTGUTY4TRZ/action/storage_attestation","attest_author":"https://pith.science/pith/PXFZYWCO32WTE7WOGTGUTY4TRZ/action/author_attestation","sign_citation":"https://pith.science/pith/PXFZYWCO32WTE7WOGTGUTY4TRZ/action/citation_signature","submit_replication":"https://pith.science/pith/PXFZYWCO32WTE7WOGTGUTY4TRZ/action/replication_record"}},"created_at":"2026-05-18T00:39:51.567652+00:00","updated_at":"2026-05-18T00:39:51.567652+00:00"}