{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:ZFD2ZISGQK2DXUUAJRHLLFBEX2","short_pith_number":"pith:ZFD2ZISG","schema_version":"1.0","canonical_sha256":"c947aca24682b43bd2804c4eb59424beb2d0484e14dd9c54cf2ac768ba8213f4","source":{"kind":"arxiv","id":"1907.13319","version":2},"attestation_state":"computed","paper":{"title":"VASSL: A Visual Analytics Toolkit for Social Spambot Labeling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI"],"primary_cat":"cs.HC","authors_text":"David S. Ebert, Jieqiong Zhao, Morteza Karimzadeh, Mosab Khayat","submitted_at":"2019-07-31T06:05:55Z","abstract_excerpt":"Social media platforms such as Twitter are filled with social spambots. Detecting these malicious accounts is essential, yet challenging, as they continually evolve and evade traditional detection techniques. In this work, we propose VASSL, a visual analytics system that assists in the process of detecting and labeling spambots. Our tool enhances the performance and scalability of manual labeling by providing multiple connected views and utilizing dimensionality reduction, sentiment analysis and topic modeling techniques, which offer new insights that enable the identification of spambots. The"},"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":"1907.13319","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2019-07-31T06:05:55Z","cross_cats_sorted":["cs.SI"],"title_canon_sha256":"158256e6a25c5a6d319195956378f1840e31d38bd5163e5f93e33fc4f8cbfe65","abstract_canon_sha256":"cc311e77a8b8ee5852cc6b5cf12f175fd7bf6d6fa9125cffba7d5266517e2c36"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:10:15.358999Z","signature_b64":"7sMDpbP3phEcKdm4jB8VGTJNsT2xn41JhGpFjsUEcs1uS1AbH2qVFt7DQS2yCHYVnqB/d4Trh0Gz3a6oOt4xAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c947aca24682b43bd2804c4eb59424beb2d0484e14dd9c54cf2ac768ba8213f4","last_reissued_at":"2026-07-05T00:10:15.358583Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:10:15.358583Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"VASSL: A Visual Analytics Toolkit for Social Spambot Labeling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI"],"primary_cat":"cs.HC","authors_text":"David S. Ebert, Jieqiong Zhao, Morteza Karimzadeh, Mosab Khayat","submitted_at":"2019-07-31T06:05:55Z","abstract_excerpt":"Social media platforms such as Twitter are filled with social spambots. Detecting these malicious accounts is essential, yet challenging, as they continually evolve and evade traditional detection techniques. In this work, we propose VASSL, a visual analytics system that assists in the process of detecting and labeling spambots. Our tool enhances the performance and scalability of manual labeling by providing multiple connected views and utilizing dimensionality reduction, sentiment analysis and topic modeling techniques, which offer new insights that enable the identification of spambots. The"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.13319","kind":"arxiv","version":2},"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/1907.13319/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":"1907.13319","created_at":"2026-07-05T00:10:15.358640+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.13319v2","created_at":"2026-07-05T00:10:15.358640+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.13319","created_at":"2026-07-05T00:10:15.358640+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZFD2ZISGQK2D","created_at":"2026-07-05T00:10:15.358640+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZFD2ZISGQK2DXUUA","created_at":"2026-07-05T00:10:15.358640+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZFD2ZISG","created_at":"2026-07-05T00:10:15.358640+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/ZFD2ZISGQK2DXUUAJRHLLFBEX2","json":"https://pith.science/pith/ZFD2ZISGQK2DXUUAJRHLLFBEX2.json","graph_json":"https://pith.science/api/pith-number/ZFD2ZISGQK2DXUUAJRHLLFBEX2/graph.json","events_json":"https://pith.science/api/pith-number/ZFD2ZISGQK2DXUUAJRHLLFBEX2/events.json","paper":"https://pith.science/paper/ZFD2ZISG"},"agent_actions":{"view_html":"https://pith.science/pith/ZFD2ZISGQK2DXUUAJRHLLFBEX2","download_json":"https://pith.science/pith/ZFD2ZISGQK2DXUUAJRHLLFBEX2.json","view_paper":"https://pith.science/paper/ZFD2ZISG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.13319&json=true","fetch_graph":"https://pith.science/api/pith-number/ZFD2ZISGQK2DXUUAJRHLLFBEX2/graph.json","fetch_events":"https://pith.science/api/pith-number/ZFD2ZISGQK2DXUUAJRHLLFBEX2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZFD2ZISGQK2DXUUAJRHLLFBEX2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZFD2ZISGQK2DXUUAJRHLLFBEX2/action/storage_attestation","attest_author":"https://pith.science/pith/ZFD2ZISGQK2DXUUAJRHLLFBEX2/action/author_attestation","sign_citation":"https://pith.science/pith/ZFD2ZISGQK2DXUUAJRHLLFBEX2/action/citation_signature","submit_replication":"https://pith.science/pith/ZFD2ZISGQK2DXUUAJRHLLFBEX2/action/replication_record"}},"created_at":"2026-07-05T00:10:15.358640+00:00","updated_at":"2026-07-05T00:10:15.358640+00:00"}