{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:WKJYQZRSRPCLZ5SKFWF7IYLNX2","short_pith_number":"pith:WKJYQZRS","schema_version":"1.0","canonical_sha256":"b2938866328bc4bcf64a2d8bf4616dbeb009342b534c21eb603fadfd8163cb0d","source":{"kind":"arxiv","id":"1509.07344","version":1},"attestation_state":"computed","paper":{"title":"Opinion mining from twitter data using evolutionary multinomial mixture models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.IR","authors_text":"Julien Jacques, Julien Velcin, Md. Abul Hasnat, St\\'ephane Bonnevay","submitted_at":"2015-09-24T12:40:12Z","abstract_excerpt":"Image of an entity can be defined as a structured and dynamic representation which can be extracted from the opinions of a group of users or population. Automatic extraction of such an image has certain importance in political science and sociology related studies, e.g., when an extended inquiry from large-scale data is required. We study the images of two politically significant entities of France. These images are constructed by analyzing the opinions collected from a well known social media called Twitter. Our goal is to build a system which can be used to automatically extract the image of"},"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":"1509.07344","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2015-09-24T12:40:12Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"c96ed0613dd6219f7bcf01585e2b7438d7abd23e6f7d3f41897ed0927e83afd9","abstract_canon_sha256":"2f269c9ed6224c340e1895d82b11c6157a3e16ead10bd32152deb9dd916ce485"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:32:09.236519Z","signature_b64":"9Y7YlcquUosWtKp2G+d+JC8o1raLf6C1zdV/fuSL1xvbIpjaldXMr0p9jty0c6U3JVEvi0WfNWu1qqrpSNtICQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b2938866328bc4bcf64a2d8bf4616dbeb009342b534c21eb603fadfd8163cb0d","last_reissued_at":"2026-05-18T01:32:09.235656Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:32:09.235656Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Opinion mining from twitter data using evolutionary multinomial mixture models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.IR","authors_text":"Julien Jacques, Julien Velcin, Md. Abul Hasnat, St\\'ephane Bonnevay","submitted_at":"2015-09-24T12:40:12Z","abstract_excerpt":"Image of an entity can be defined as a structured and dynamic representation which can be extracted from the opinions of a group of users or population. Automatic extraction of such an image has certain importance in political science and sociology related studies, e.g., when an extended inquiry from large-scale data is required. We study the images of two politically significant entities of France. These images are constructed by analyzing the opinions collected from a well known social media called Twitter. Our goal is to build a system which can be used to automatically extract the image of"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.07344","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":"1509.07344","created_at":"2026-05-18T01:32:09.235801+00:00"},{"alias_kind":"arxiv_version","alias_value":"1509.07344v1","created_at":"2026-05-18T01:32:09.235801+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1509.07344","created_at":"2026-05-18T01:32:09.235801+00:00"},{"alias_kind":"pith_short_12","alias_value":"WKJYQZRSRPCL","created_at":"2026-05-18T12:29:47.479230+00:00"},{"alias_kind":"pith_short_16","alias_value":"WKJYQZRSRPCLZ5SK","created_at":"2026-05-18T12:29:47.479230+00:00"},{"alias_kind":"pith_short_8","alias_value":"WKJYQZRS","created_at":"2026-05-18T12:29:47.479230+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/WKJYQZRSRPCLZ5SKFWF7IYLNX2","json":"https://pith.science/pith/WKJYQZRSRPCLZ5SKFWF7IYLNX2.json","graph_json":"https://pith.science/api/pith-number/WKJYQZRSRPCLZ5SKFWF7IYLNX2/graph.json","events_json":"https://pith.science/api/pith-number/WKJYQZRSRPCLZ5SKFWF7IYLNX2/events.json","paper":"https://pith.science/paper/WKJYQZRS"},"agent_actions":{"view_html":"https://pith.science/pith/WKJYQZRSRPCLZ5SKFWF7IYLNX2","download_json":"https://pith.science/pith/WKJYQZRSRPCLZ5SKFWF7IYLNX2.json","view_paper":"https://pith.science/paper/WKJYQZRS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1509.07344&json=true","fetch_graph":"https://pith.science/api/pith-number/WKJYQZRSRPCLZ5SKFWF7IYLNX2/graph.json","fetch_events":"https://pith.science/api/pith-number/WKJYQZRSRPCLZ5SKFWF7IYLNX2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WKJYQZRSRPCLZ5SKFWF7IYLNX2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WKJYQZRSRPCLZ5SKFWF7IYLNX2/action/storage_attestation","attest_author":"https://pith.science/pith/WKJYQZRSRPCLZ5SKFWF7IYLNX2/action/author_attestation","sign_citation":"https://pith.science/pith/WKJYQZRSRPCLZ5SKFWF7IYLNX2/action/citation_signature","submit_replication":"https://pith.science/pith/WKJYQZRSRPCLZ5SKFWF7IYLNX2/action/replication_record"}},"created_at":"2026-05-18T01:32:09.235801+00:00","updated_at":"2026-05-18T01:32:09.235801+00:00"}