Follow the leader: Documents on the leading edge of semantic change get more citations

Abstract

Diachronic word embeddings—vector representations of words over time—offer remarkable insights into the evolution of language and provide a tool for quantifying sociocultural change from text documents. Prior work has used such embeddings to identify shifts in the meaning of individual words. However, simply knowing that a word has changed in meaning is insufficient to identify the instances of word usage that convey the historical meaning or the newer meaning. In this study, we link diachronic word embeddings to documents, by situating those documents as leaders or laggards with respect to ongoing semantic changes. Specifically, we propose a novel method to quantify the degree of semantic progressiveness in each word usage, and then show how these usages can be aggregated to obtain scores for each document. We analyze two large collections of documents, representing legal opinions and scientific articles. Documents that are scored as semantically progressive receive a larger number of citations, indicating that they are especially influential. Our work thus provides a new technique for identifying lexical semantic leaders and demonstrates a new link between progressive use of language and influence in a citation network.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 22, 2020
Source ID
10.1002/asi.24421

Entities

People

  • Jacob Eisenstein
  • Kristina Lerman
  • Sandeep Soni

Organizations

  • Air Force Office of Scientific Research
  • Defense Advanced Research Projects Agency
  • Division of Information and Intelligent Systems
  • Georgia Tech
  • Google
  • University of Southern California

Tags

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Systems Analysis and Design