A Unified Model of Text and Citations for Topic-Specific Citation Networks

TL;DR

This paper introduces the paragraph-citation topic model (PCTM), a unified approach that jointly analyzes citation networks and document texts to better understand the semantic contexts of citations across domains.

Contribution

The PCTM extends traditional topic models by assigning topics at the paragraph level, capturing the diverse semantic contexts of citations within documents.

Findings

Citations within documents often cover multiple substantive areas.

Citations to individual documents exhibit significant topical diversity.

Empirical analysis on Supreme Court opinions reveals complex citation patterns.

Abstract

Social scientists analyze citation networks to study how documents influence subsequent work across various domains such as judicial politics and international relations. However, conventional approaches that summarize document attributes in citation networks often overlook the diverse semantic contexts in which citations occur. This paper develops the paragraph-citation topic model (PCTM), which analyzes citation networks and document texts jointly. The PCTM extends conventional topic models by assigning topics to paragraphs of citing documents, allowing citations to share topics with their embedding paragraphs. Our empirical analysis of U.S. Supreme Court opinions in the privacy issue domain, which includes cases on reproductive rights, demonstrates that citations within individual documents frequently span multiple substantive areas, and citations to individual documents show considerable topical diversity.