{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:5WQY46BLHSMTPQ4X26VX7S73SO","short_pith_number":"pith:5WQY46BL","schema_version":"1.0","canonical_sha256":"eda18e782b3c9937c397d7ab7fcbfb93acec843317c74c638d35981df0997f43","source":{"kind":"arxiv","id":"2010.11851","version":1},"attestation_state":"computed","paper":{"title":"Hawkes Process Classification through Discriminative Modeling of Text","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Manisha Dubey, Michal Lukasik, P.K. Srijith, Rohan Tondulkar","submitted_at":"2020-10-22T16:42:48Z","abstract_excerpt":"Social media has provided a platform for users to gather and share information and stay updated with the news. Such networks also provide a platform to users where they can engage in conversations. However, such micro-blogging platforms like Twitter restricts the length of text. Due to paucity of sufficient word occurrences in such posts, classification of this information is a challenging task using standard tools of natural language processing (NLP). Moreover, high complexity and dynamics of the posts in social media makes text classification a challenging problem. However, considering addit"},"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":"2010.11851","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2020-10-22T16:42:48Z","cross_cats_sorted":[],"title_canon_sha256":"4184c01efcd8128a5fac96379e295cb5d01732b54b9606d1f53c7557a0f2e5a4","abstract_canon_sha256":"f34da6bedb4cc0c39d07b78bea3937bf220f0838883240ee55e56e5161ed1a15"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:45:21.504723Z","signature_b64":"s9HaKrcO/ky7WIt7n8YxC28c3PN7AoC9KvCP0tOzsjW9QWG/PDDxa1wurXXmHWHHSgifrhYceupAS5Cfol8/Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eda18e782b3c9937c397d7ab7fcbfb93acec843317c74c638d35981df0997f43","last_reissued_at":"2026-07-05T01:45:21.504392Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:45:21.504392Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Hawkes Process Classification through Discriminative Modeling of Text","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Manisha Dubey, Michal Lukasik, P.K. Srijith, Rohan Tondulkar","submitted_at":"2020-10-22T16:42:48Z","abstract_excerpt":"Social media has provided a platform for users to gather and share information and stay updated with the news. Such networks also provide a platform to users where they can engage in conversations. However, such micro-blogging platforms like Twitter restricts the length of text. Due to paucity of sufficient word occurrences in such posts, classification of this information is a challenging task using standard tools of natural language processing (NLP). Moreover, high complexity and dynamics of the posts in social media makes text classification a challenging problem. However, considering addit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.11851","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/2010.11851/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":"2010.11851","created_at":"2026-07-05T01:45:21.504446+00:00"},{"alias_kind":"arxiv_version","alias_value":"2010.11851v1","created_at":"2026-07-05T01:45:21.504446+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.11851","created_at":"2026-07-05T01:45:21.504446+00:00"},{"alias_kind":"pith_short_12","alias_value":"5WQY46BLHSMT","created_at":"2026-07-05T01:45:21.504446+00:00"},{"alias_kind":"pith_short_16","alias_value":"5WQY46BLHSMTPQ4X","created_at":"2026-07-05T01:45:21.504446+00:00"},{"alias_kind":"pith_short_8","alias_value":"5WQY46BL","created_at":"2026-07-05T01:45:21.504446+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/5WQY46BLHSMTPQ4X26VX7S73SO","json":"https://pith.science/pith/5WQY46BLHSMTPQ4X26VX7S73SO.json","graph_json":"https://pith.science/api/pith-number/5WQY46BLHSMTPQ4X26VX7S73SO/graph.json","events_json":"https://pith.science/api/pith-number/5WQY46BLHSMTPQ4X26VX7S73SO/events.json","paper":"https://pith.science/paper/5WQY46BL"},"agent_actions":{"view_html":"https://pith.science/pith/5WQY46BLHSMTPQ4X26VX7S73SO","download_json":"https://pith.science/pith/5WQY46BLHSMTPQ4X26VX7S73SO.json","view_paper":"https://pith.science/paper/5WQY46BL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2010.11851&json=true","fetch_graph":"https://pith.science/api/pith-number/5WQY46BLHSMTPQ4X26VX7S73SO/graph.json","fetch_events":"https://pith.science/api/pith-number/5WQY46BLHSMTPQ4X26VX7S73SO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5WQY46BLHSMTPQ4X26VX7S73SO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5WQY46BLHSMTPQ4X26VX7S73SO/action/storage_attestation","attest_author":"https://pith.science/pith/5WQY46BLHSMTPQ4X26VX7S73SO/action/author_attestation","sign_citation":"https://pith.science/pith/5WQY46BLHSMTPQ4X26VX7S73SO/action/citation_signature","submit_replication":"https://pith.science/pith/5WQY46BLHSMTPQ4X26VX7S73SO/action/replication_record"}},"created_at":"2026-07-05T01:45:21.504446+00:00","updated_at":"2026-07-05T01:45:21.504446+00:00"}