Detecting Privileged Documents by Ranking Connected Network Entities

Fuente: arXiv
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Autori principali: Zhang, Jianping, Qin, Han, Huber-Fliflet, Nathaniel
Natura: Preprint
Pubblicazione: 2025
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author Zhang, Jianping
Qin, Han
Huber-Fliflet, Nathaniel
author_facet Zhang, Jianping
Qin, Han
Huber-Fliflet, Nathaniel
contents This paper presents a link analysis approach for identifying privileged documents by constructing a network of human entities derived from email header metadata. Entities are classified as either counsel or non-counsel based on a predefined list of known legal professionals. The core assumption is that individuals with frequent interactions with lawyers are more likely to participate in privileged communications. To quantify this likelihood, an algorithm assigns a score to each entity within the network. By utilizing both entity scores and the strength of their connections, the method enhances the identification of privileged documents. Experimental results demonstrate the algorithm's effectiveness in ranking legal entities for privileged document detection.
format Preprint
id arxiv_https___arxiv_org_abs_2512_08073
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Detecting Privileged Documents by Ranking Connected Network Entities
Zhang, Jianping
Qin, Han
Huber-Fliflet, Nathaniel
Information Retrieval
This paper presents a link analysis approach for identifying privileged documents by constructing a network of human entities derived from email header metadata. Entities are classified as either counsel or non-counsel based on a predefined list of known legal professionals. The core assumption is that individuals with frequent interactions with lawyers are more likely to participate in privileged communications. To quantify this likelihood, an algorithm assigns a score to each entity within the network. By utilizing both entity scores and the strength of their connections, the method enhances the identification of privileged documents. Experimental results demonstrate the algorithm's effectiveness in ranking legal entities for privileged document detection.
title Detecting Privileged Documents by Ranking Connected Network Entities
topic Information Retrieval
url https://arxiv.org/abs/2512.08073