Detecting Privileged Documents by Ranking Connected Network Entities

• URL: http://arxiv.org/abs/2512.08073v1
• Date: Mon, 08 Dec 2025 22:16:54 GMT
• Title: Detecting Privileged Documents by Ranking Connected Network Entities
• Authors: Jianping Zhang, Han Qin, Nathaniel Huber-Fliflet,
• Abstract summary: This paper presents a link analysis approach for identifying privileged documents by constructing a network of human entities derived from email header metadata.<n>The core assumption is that individuals with frequent interactions with lawyers are more likely to participate in privileged communications.<n> Experimental results demonstrate the algorithm's effectiveness in ranking legal entities for privileged document detection.
• Score: 6.208621325426645
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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.

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