{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:RBLS3LFVML2FTT7XXLZEE62FIF","short_pith_number":"pith:RBLS3LFV","schema_version":"1.0","canonical_sha256":"88572dacb562f459cff7baf2427b45415189f598b6aab6920761e53ae5a0ebaa","source":{"kind":"arxiv","id":"2212.06765","version":1},"attestation_state":"computed","paper":{"title":"Earthquake Impact Analysis Based on Text Mining and Social Media Analytics","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG","cs.SI"],"primary_cat":"cs.CL","authors_text":"Hong-Zheng Shi, Jia-Rui Lin, Xin-Zheng Lu, Yu-Cheng Zhou, Zhe Zheng","submitted_at":"2022-12-12T13:51:07Z","abstract_excerpt":"Earthquakes have a deep impact on wide areas, and emergency rescue operations may benefit from social media information about the scope and extent of the disaster. Therefore, this work presents a text miningbased approach to collect and analyze social media data for early earthquake impact analysis. First, disasterrelated microblogs are collected from the Sina microblog based on crawler technology. Then, after data cleaning a series of analyses are conducted including (1) the hot words analysis, (2) the trend of the number of microblogs, (3) the trend of public opinion sentiment, and (4) a key"},"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":"2212.06765","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-12-12T13:51:07Z","cross_cats_sorted":["cs.LG","cs.SI"],"title_canon_sha256":"98f58c547ad526f1fcb7cec9c77532bd0575bc3b5a5d4b54dcbe7afb03dff07e","abstract_canon_sha256":"7711cc7ed842199498d001cd043c9de69a6272fab1b00e065497e2f0fda0151a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:24:54.359714Z","signature_b64":"PvhdN4Lf5EUsUuxGdT5LVWKh0U/TDT826IDLOyJ7Ewe0KGyUx6qBYO3oz2F5A93EVcq6onc2Zu2jMTuNGVB6DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"88572dacb562f459cff7baf2427b45415189f598b6aab6920761e53ae5a0ebaa","last_reissued_at":"2026-07-05T05:24:54.359324Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:24:54.359324Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Earthquake Impact Analysis Based on Text Mining and Social Media Analytics","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG","cs.SI"],"primary_cat":"cs.CL","authors_text":"Hong-Zheng Shi, Jia-Rui Lin, Xin-Zheng Lu, Yu-Cheng Zhou, Zhe Zheng","submitted_at":"2022-12-12T13:51:07Z","abstract_excerpt":"Earthquakes have a deep impact on wide areas, and emergency rescue operations may benefit from social media information about the scope and extent of the disaster. Therefore, this work presents a text miningbased approach to collect and analyze social media data for early earthquake impact analysis. First, disasterrelated microblogs are collected from the Sina microblog based on crawler technology. Then, after data cleaning a series of analyses are conducted including (1) the hot words analysis, (2) the trend of the number of microblogs, (3) the trend of public opinion sentiment, and (4) a key"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.06765","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/2212.06765/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":"2212.06765","created_at":"2026-07-05T05:24:54.359384+00:00"},{"alias_kind":"arxiv_version","alias_value":"2212.06765v1","created_at":"2026-07-05T05:24:54.359384+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.06765","created_at":"2026-07-05T05:24:54.359384+00:00"},{"alias_kind":"pith_short_12","alias_value":"RBLS3LFVML2F","created_at":"2026-07-05T05:24:54.359384+00:00"},{"alias_kind":"pith_short_16","alias_value":"RBLS3LFVML2FTT7X","created_at":"2026-07-05T05:24:54.359384+00:00"},{"alias_kind":"pith_short_8","alias_value":"RBLS3LFV","created_at":"2026-07-05T05:24:54.359384+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/RBLS3LFVML2FTT7XXLZEE62FIF","json":"https://pith.science/pith/RBLS3LFVML2FTT7XXLZEE62FIF.json","graph_json":"https://pith.science/api/pith-number/RBLS3LFVML2FTT7XXLZEE62FIF/graph.json","events_json":"https://pith.science/api/pith-number/RBLS3LFVML2FTT7XXLZEE62FIF/events.json","paper":"https://pith.science/paper/RBLS3LFV"},"agent_actions":{"view_html":"https://pith.science/pith/RBLS3LFVML2FTT7XXLZEE62FIF","download_json":"https://pith.science/pith/RBLS3LFVML2FTT7XXLZEE62FIF.json","view_paper":"https://pith.science/paper/RBLS3LFV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2212.06765&json=true","fetch_graph":"https://pith.science/api/pith-number/RBLS3LFVML2FTT7XXLZEE62FIF/graph.json","fetch_events":"https://pith.science/api/pith-number/RBLS3LFVML2FTT7XXLZEE62FIF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RBLS3LFVML2FTT7XXLZEE62FIF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RBLS3LFVML2FTT7XXLZEE62FIF/action/storage_attestation","attest_author":"https://pith.science/pith/RBLS3LFVML2FTT7XXLZEE62FIF/action/author_attestation","sign_citation":"https://pith.science/pith/RBLS3LFVML2FTT7XXLZEE62FIF/action/citation_signature","submit_replication":"https://pith.science/pith/RBLS3LFVML2FTT7XXLZEE62FIF/action/replication_record"}},"created_at":"2026-07-05T05:24:54.359384+00:00","updated_at":"2026-07-05T05:24:54.359384+00:00"}