{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:QUPX243KCOKYNWDBYBTDMM2XRX","short_pith_number":"pith:QUPX243K","schema_version":"1.0","canonical_sha256":"851f7d736a139586d861c0663633578dd942795f2a0f23e9c384ad4361049d0e","source":{"kind":"arxiv","id":"1907.07768","version":1},"attestation_state":"computed","paper":{"title":"A Novel Approach for Detection and Ranking of Trendy and Emerging Cyber Threat Events in Twitter Streams","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.LG","cs.SI","stat.ML"],"primary_cat":"cs.IR","authors_text":"Avishek Bose, Carlos Aguirre, Vahid Behzadan, William H. Hsu","submitted_at":"2019-07-12T22:17:17Z","abstract_excerpt":"We present a new machine learning and text information extraction approach to detection of cyber threat events in Twitter that are novel (previously non-extant) and developing (marked by significance with respect to similarity with a previously detected event). While some existing approaches to event detection measure novelty and trendiness, typically as independent criteria and occasionally as a holistic measure, this work focuses on detecting both novel and developing events using an unsupervised machine learning approach. Furthermore, our proposed approach enables the ranking of cyber threa"},"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":"1907.07768","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-07-12T22:17:17Z","cross_cats_sorted":["cs.CR","cs.LG","cs.SI","stat.ML"],"title_canon_sha256":"0023fd08633cace8184657f8421bcdc8b4ab6b113971ace9ae9f7af20132ea06","abstract_canon_sha256":"34279da314f3b34e040316a1af8494751767fcc0bce02a40d2c1ed8064198d70"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:16.378241Z","signature_b64":"O0+aeNTxaf2gJPv9RL+WMFThPN2pLNcDexkzc4/A3cHW5fI1ma/r1/Gl3hTdo61eFCG3I/huEMmUgu21HxUPCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"851f7d736a139586d861c0663633578dd942795f2a0f23e9c384ad4361049d0e","last_reissued_at":"2026-05-17T23:40:16.377512Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:16.377512Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Novel Approach for Detection and Ranking of Trendy and Emerging Cyber Threat Events in Twitter Streams","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.LG","cs.SI","stat.ML"],"primary_cat":"cs.IR","authors_text":"Avishek Bose, Carlos Aguirre, Vahid Behzadan, William H. Hsu","submitted_at":"2019-07-12T22:17:17Z","abstract_excerpt":"We present a new machine learning and text information extraction approach to detection of cyber threat events in Twitter that are novel (previously non-extant) and developing (marked by significance with respect to similarity with a previously detected event). While some existing approaches to event detection measure novelty and trendiness, typically as independent criteria and occasionally as a holistic measure, this work focuses on detecting both novel and developing events using an unsupervised machine learning approach. Furthermore, our proposed approach enables the ranking of cyber threa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.07768","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":"1907.07768","created_at":"2026-05-17T23:40:16.377628+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.07768v1","created_at":"2026-05-17T23:40:16.377628+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.07768","created_at":"2026-05-17T23:40:16.377628+00:00"},{"alias_kind":"pith_short_12","alias_value":"QUPX243KCOKY","created_at":"2026-05-18T12:33:27.125529+00:00"},{"alias_kind":"pith_short_16","alias_value":"QUPX243KCOKYNWDB","created_at":"2026-05-18T12:33:27.125529+00:00"},{"alias_kind":"pith_short_8","alias_value":"QUPX243K","created_at":"2026-05-18T12:33:27.125529+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/QUPX243KCOKYNWDBYBTDMM2XRX","json":"https://pith.science/pith/QUPX243KCOKYNWDBYBTDMM2XRX.json","graph_json":"https://pith.science/api/pith-number/QUPX243KCOKYNWDBYBTDMM2XRX/graph.json","events_json":"https://pith.science/api/pith-number/QUPX243KCOKYNWDBYBTDMM2XRX/events.json","paper":"https://pith.science/paper/QUPX243K"},"agent_actions":{"view_html":"https://pith.science/pith/QUPX243KCOKYNWDBYBTDMM2XRX","download_json":"https://pith.science/pith/QUPX243KCOKYNWDBYBTDMM2XRX.json","view_paper":"https://pith.science/paper/QUPX243K","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.07768&json=true","fetch_graph":"https://pith.science/api/pith-number/QUPX243KCOKYNWDBYBTDMM2XRX/graph.json","fetch_events":"https://pith.science/api/pith-number/QUPX243KCOKYNWDBYBTDMM2XRX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QUPX243KCOKYNWDBYBTDMM2XRX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QUPX243KCOKYNWDBYBTDMM2XRX/action/storage_attestation","attest_author":"https://pith.science/pith/QUPX243KCOKYNWDBYBTDMM2XRX/action/author_attestation","sign_citation":"https://pith.science/pith/QUPX243KCOKYNWDBYBTDMM2XRX/action/citation_signature","submit_replication":"https://pith.science/pith/QUPX243KCOKYNWDBYBTDMM2XRX/action/replication_record"}},"created_at":"2026-05-17T23:40:16.377628+00:00","updated_at":"2026-05-17T23:40:16.377628+00:00"}