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Measuring discursive influence across scholarship
Assessing scholarly influence is critical for understanding the collective system of scholarship and the history of academic inquiry. Influence is multifaceted, and citations reveal only part of it. Citation counts exhibit preferential attachment and follow a rigid “news cycle” that can miss sustain...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5879694/ https://www.ncbi.nlm.nih.gov/pubmed/29531061 http://dx.doi.org/10.1073/pnas.1719792115 |
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author | Gerow, Aaron Hu, Yuening Boyd-Graber, Jordan Blei, David M. Evans, James A. |
author_facet | Gerow, Aaron Hu, Yuening Boyd-Graber, Jordan Blei, David M. Evans, James A. |
author_sort | Gerow, Aaron |
collection | PubMed |
description | Assessing scholarly influence is critical for understanding the collective system of scholarship and the history of academic inquiry. Influence is multifaceted, and citations reveal only part of it. Citation counts exhibit preferential attachment and follow a rigid “news cycle” that can miss sustained and indirect forms of influence. Building on dynamic topic models that track distributional shifts in discourse over time, we introduce a variant that incorporates features, such as authorship, affiliation, and publication venue, to assess how these contexts interact with content to shape future scholarship. We perform in-depth analyses on collections of physics research (500,000 abstracts; 102 years) and scholarship generally (JSTOR repository: 2 million full-text articles; 130 years). Our measure of document influence helps predict citations and shows how outcomes, such as winning a Nobel Prize or affiliation with a highly ranked institution, boost influence. Analysis of citations alongside discursive influence reveals that citations tend to credit authors who persist in their fields over time and discount credit for works that are influential over many topics or are “ahead of their time.” In this way, our measures provide a way to acknowledge diverse contributions that take longer and travel farther to achieve scholarly appreciation, enabling us to correct citation biases and enhance sensitivity to the full spectrum of scholarly impact. |
format | Online Article Text |
id | pubmed-5879694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-58796942018-04-03 Measuring discursive influence across scholarship Gerow, Aaron Hu, Yuening Boyd-Graber, Jordan Blei, David M. Evans, James A. Proc Natl Acad Sci U S A Social Sciences Assessing scholarly influence is critical for understanding the collective system of scholarship and the history of academic inquiry. Influence is multifaceted, and citations reveal only part of it. Citation counts exhibit preferential attachment and follow a rigid “news cycle” that can miss sustained and indirect forms of influence. Building on dynamic topic models that track distributional shifts in discourse over time, we introduce a variant that incorporates features, such as authorship, affiliation, and publication venue, to assess how these contexts interact with content to shape future scholarship. We perform in-depth analyses on collections of physics research (500,000 abstracts; 102 years) and scholarship generally (JSTOR repository: 2 million full-text articles; 130 years). Our measure of document influence helps predict citations and shows how outcomes, such as winning a Nobel Prize or affiliation with a highly ranked institution, boost influence. Analysis of citations alongside discursive influence reveals that citations tend to credit authors who persist in their fields over time and discount credit for works that are influential over many topics or are “ahead of their time.” In this way, our measures provide a way to acknowledge diverse contributions that take longer and travel farther to achieve scholarly appreciation, enabling us to correct citation biases and enhance sensitivity to the full spectrum of scholarly impact. National Academy of Sciences 2018-03-27 2018-03-12 /pmc/articles/PMC5879694/ /pubmed/29531061 http://dx.doi.org/10.1073/pnas.1719792115 Text en Copyright © 2018 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Social Sciences Gerow, Aaron Hu, Yuening Boyd-Graber, Jordan Blei, David M. Evans, James A. Measuring discursive influence across scholarship |
title | Measuring discursive influence across scholarship |
title_full | Measuring discursive influence across scholarship |
title_fullStr | Measuring discursive influence across scholarship |
title_full_unstemmed | Measuring discursive influence across scholarship |
title_short | Measuring discursive influence across scholarship |
title_sort | measuring discursive influence across scholarship |
topic | Social Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5879694/ https://www.ncbi.nlm.nih.gov/pubmed/29531061 http://dx.doi.org/10.1073/pnas.1719792115 |
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