{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:KF4KUCWKJSVF6ASOUEPAQ7BGIM","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"5e1095a9dcf540c076340347dc4bf2d3c604ee8d9b7bf7f500e6f891d7216537","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2021-10-04T04:51:11Z","title_canon_sha256":"ab55f1f376f9e6ab0cc5eb37efee1233f1d849404e0eac981e2de4cf363b29a6"},"schema_version":"1.0","source":{"id":"2110.01186","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.01186","created_at":"2026-07-05T04:54:16Z"},{"alias_kind":"arxiv_version","alias_value":"2110.01186v3","created_at":"2026-07-05T04:54:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.01186","created_at":"2026-07-05T04:54:16Z"},{"alias_kind":"pith_short_12","alias_value":"KF4KUCWKJSVF","created_at":"2026-07-05T04:54:16Z"},{"alias_kind":"pith_short_16","alias_value":"KF4KUCWKJSVF6ASO","created_at":"2026-07-05T04:54:16Z"},{"alias_kind":"pith_short_8","alias_value":"KF4KUCWK","created_at":"2026-07-05T04:54:16Z"}],"graph_snapshots":[{"event_id":"sha256:b9149b3f439f76bcbaad2a2bc796a7552c64c3a9f31142de90d678eb6546f093","target":"graph","created_at":"2026-07-05T04:54:16Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2110.01186/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Personality detection is an old topic in psychology and Automatic Personality Prediction (or Perception) (APP) is the automated (computationally) forecasting of the personality on different types of human generated/exchanged contents (such as text, speech, image, video). The principal objective of this study is to offer a shallow (overall) review of natural language processing approaches on APP since 2010. With the advent of deep learning and following it transfer-learning and pre-trained model in NLP, APP research area has been a hot topic, so in this review, methods are categorized into thre","authors_text":"Ali-Reza Feizi-Derakhshi, Elnaz Zafarni-Moattar, Majid Ramezani, Mehrdad Ranjbar-Khadivi, Meysam Asgari-Chenaghlu, Mohammad-Reza Feizi-Derakhshi, Narjes Nikzad-Khasmakhi, Taymaz Akan (Rahkar-Farshi), Zoleikha Jahanbakhsh-Naghadeh","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2021-10-04T04:51:11Z","title":"Text-based automatic personality prediction: A bibliographic review"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.01186","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:1ffb0e5c3c0970e20aad8b0bc727dd7fd2c7a9c7b8a8bb1da8472ad3b45278fd","target":"record","created_at":"2026-07-05T04:54:16Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"5e1095a9dcf540c076340347dc4bf2d3c604ee8d9b7bf7f500e6f891d7216537","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2021-10-04T04:51:11Z","title_canon_sha256":"ab55f1f376f9e6ab0cc5eb37efee1233f1d849404e0eac981e2de4cf363b29a6"},"schema_version":"1.0","source":{"id":"2110.01186","kind":"arxiv","version":3}},"canonical_sha256":"5178aa0aca4caa5f024ea11e087c26431d3da7a74c04c4dc1696bc517662df0b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5178aa0aca4caa5f024ea11e087c26431d3da7a74c04c4dc1696bc517662df0b","first_computed_at":"2026-07-05T04:54:16.203853Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:54:16.203853Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gjYBqmvgQNIje04sQ+5hvKpw9iptkeC2C3c6YD8g6m4TbvhL5JuSJVPyAAdSBMiDeRgUc9qN0yS6lrRSdaknAw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:54:16.204268Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.01186","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1ffb0e5c3c0970e20aad8b0bc727dd7fd2c7a9c7b8a8bb1da8472ad3b45278fd","sha256:b9149b3f439f76bcbaad2a2bc796a7552c64c3a9f31142de90d678eb6546f093"],"state_sha256":"17b4831572b02f65fa9688ee984cd17047eb6fd69fefddd587c605845ad44be3"}