{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:3AQTQO3E7CZ7X4Y6HAPYKMDR45","short_pith_number":"pith:3AQTQO3E","schema_version":"1.0","canonical_sha256":"d821383b64f8b3fbf31e381f853071e7513e9639fcfcccf1876923d581345c2f","source":{"kind":"arxiv","id":"2309.05607","version":1},"attestation_state":"computed","paper":{"title":"Creating a Systematic ESG (Environmental Social Governance) Scoring System Using Social Network Analysis and Machine Learning for More Sustainable Company Practices","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.SI","authors_text":"Aarav Patel, Peter Gloor","submitted_at":"2023-09-07T20:03:45Z","abstract_excerpt":"Environmental Social Governance (ESG) is a widely used metric that measures the sustainability of a company practices. Currently, ESG is determined using self-reported corporate filings, which allows companies to portray themselves in an artificially positive light. As a result, ESG evaluation is subjective and inconsistent across raters, giving executives mixed signals on what to improve. This project aims to create a data-driven ESG evaluation system that can provide better guidance and more systemized scores by incorporating social sentiment. Social sentiment allows for more balanced perspe"},"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":"2309.05607","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.SI","submitted_at":"2023-09-07T20:03:45Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"abcf2b503f7c4a476e889f4408dcce88af7db29c1d41bc9d7ff4025987ec815b","abstract_canon_sha256":"a121712681977da7e97fba0a594ad821f4475cd8d15f098dfd7f6a0cb6531a20"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:49:37.619978Z","signature_b64":"5TFdsIBUkB1FrdT7xoHepP8K3qx3GG136zdTxd6FziTu5lmlgR6s89unmyM43sk02ilDJeVZnD5qvJX8bvFwCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d821383b64f8b3fbf31e381f853071e7513e9639fcfcccf1876923d581345c2f","last_reissued_at":"2026-07-05T06:49:37.619350Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:49:37.619350Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Creating a Systematic ESG (Environmental Social Governance) Scoring System Using Social Network Analysis and Machine Learning for More Sustainable Company Practices","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.SI","authors_text":"Aarav Patel, Peter Gloor","submitted_at":"2023-09-07T20:03:45Z","abstract_excerpt":"Environmental Social Governance (ESG) is a widely used metric that measures the sustainability of a company practices. Currently, ESG is determined using self-reported corporate filings, which allows companies to portray themselves in an artificially positive light. As a result, ESG evaluation is subjective and inconsistent across raters, giving executives mixed signals on what to improve. This project aims to create a data-driven ESG evaluation system that can provide better guidance and more systemized scores by incorporating social sentiment. Social sentiment allows for more balanced perspe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.05607","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/2309.05607/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":"2309.05607","created_at":"2026-07-05T06:49:37.619419+00:00"},{"alias_kind":"arxiv_version","alias_value":"2309.05607v1","created_at":"2026-07-05T06:49:37.619419+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.05607","created_at":"2026-07-05T06:49:37.619419+00:00"},{"alias_kind":"pith_short_12","alias_value":"3AQTQO3E7CZ7","created_at":"2026-07-05T06:49:37.619419+00:00"},{"alias_kind":"pith_short_16","alias_value":"3AQTQO3E7CZ7X4Y6","created_at":"2026-07-05T06:49:37.619419+00:00"},{"alias_kind":"pith_short_8","alias_value":"3AQTQO3E","created_at":"2026-07-05T06:49:37.619419+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/3AQTQO3E7CZ7X4Y6HAPYKMDR45","json":"https://pith.science/pith/3AQTQO3E7CZ7X4Y6HAPYKMDR45.json","graph_json":"https://pith.science/api/pith-number/3AQTQO3E7CZ7X4Y6HAPYKMDR45/graph.json","events_json":"https://pith.science/api/pith-number/3AQTQO3E7CZ7X4Y6HAPYKMDR45/events.json","paper":"https://pith.science/paper/3AQTQO3E"},"agent_actions":{"view_html":"https://pith.science/pith/3AQTQO3E7CZ7X4Y6HAPYKMDR45","download_json":"https://pith.science/pith/3AQTQO3E7CZ7X4Y6HAPYKMDR45.json","view_paper":"https://pith.science/paper/3AQTQO3E","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2309.05607&json=true","fetch_graph":"https://pith.science/api/pith-number/3AQTQO3E7CZ7X4Y6HAPYKMDR45/graph.json","fetch_events":"https://pith.science/api/pith-number/3AQTQO3E7CZ7X4Y6HAPYKMDR45/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3AQTQO3E7CZ7X4Y6HAPYKMDR45/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3AQTQO3E7CZ7X4Y6HAPYKMDR45/action/storage_attestation","attest_author":"https://pith.science/pith/3AQTQO3E7CZ7X4Y6HAPYKMDR45/action/author_attestation","sign_citation":"https://pith.science/pith/3AQTQO3E7CZ7X4Y6HAPYKMDR45/action/citation_signature","submit_replication":"https://pith.science/pith/3AQTQO3E7CZ7X4Y6HAPYKMDR45/action/replication_record"}},"created_at":"2026-07-05T06:49:37.619419+00:00","updated_at":"2026-07-05T06:49:37.619419+00:00"}