{"as_of":"2026-08-09T13:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:bb9e7d5c67f3da677829a68ec4546da4d95bd0503e05407f09ae2d5679dea3c7","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T19:34:08.337310Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-08T19:34:08.421161Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2105.01402","last_updated":"2021-05-04T10:27:37Z","snapshot_observed_at":"2026-08-08T07:49:11.863435Z","submitted_at":"2021-05-04T10:27:37Z","title":"Using Twitter Attribute Information to Predict Stock Prices","version":1},"cited_work":{"arxiv_id":"2105.01402","doi":null,"metadata_source":"pith","pith_arxiv_id":"2105.01402","snapshot_observed_at":"2026-08-08T19:34:08.421161Z","title":"Using Twitter Attribute Information to Predict Stock Prices","venue":"cs.LG","work_id":"1cbe258d-7f19-4c44-928e-2cb0811db430","year":2021},"citing_paper":{"arxiv_id":"2502.05403","last_updated":"2025-02-08T01:48:10Z","snapshot_observed_at":"2026-08-08T19:28:01.357254Z","submitted_at":"2025-02-08T01:48:10Z","title":"Analyzing public sentiment to gauge key stock events and determine volatility in conjunction with time and options premiums","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-08T19:34:08.337310Z"},"links":{"cited_paper":"/paper/2105.01402","citing_paper":"/paper/2502.05403"},"observation_digest":"sha256:e1c6a0c64941d69c934d4b9083837c3e318b8d2b4bbb7e88a8a994581294cb67","observation_id":"c215e53f-e65e-493f-85a3-aa335681cad7","resolution":{"observed_at":"2026-08-08T19:34:08.425109Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2105.01402/citation-record","integrity":"/paper/2105.01402/integrity","json":"/paper/2105.01402/citation-record.json","paper":"/paper/2105.01402"},"outbound":[],"paper":{"arxiv_id":"2105.01402","last_updated":"2021-05-04T10:27:37Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-08T07:49:11.863435Z","submitted_at":"2021-05-04T10:27:37Z","title":"Using Twitter Attribute Information to Predict Stock Prices"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2105.01402."}