转移档案凝视:利用计算方法揭示媒体历史叙事的案例

IF 0.4 Q4 COMMUNICATION

American Journalism Pub Date : 2023-04-03 DOI:10.1080/08821127.2023.2199254

Mary V. Heckman, Giulia Taurino

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引用次数: 0

摘要

摘要通过对一项新兴技术的跨学科研究，本文努力应对使用一种名为机器学习的人工智能来编目和理解媒体历史学家现在可以获得的数字材料数量的机遇和挑战。作者是一名新闻学教授和人工智能研究人员，他们描述了他们最近的跨学科努力，利用机器学习来探索《波士顿环球报》捐赠给他们机构的大约570万张摄影底片。他们的工作阐明了新兴计算方法在揭示更完整历史方面的巨大力量，但也提醒人们应该谨慎使用这些工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Shifting the Archival Gaze: A Case for Leveraging Computational Methods to Uncover Media History Narratives

Abstract Through an interdisciplinary examination of a bourgeoning technology, this essay grapples with the opportunities and challenges of using a type of artificial intelligence called machine learning to catalog and make sense of the unpreceded number of digital materials now available to media historians. The authors—a journalism professor and an AI researcher—describe their recent interdisciplinary efforts to use machine learning to explore a collection of roughly 5.7 million photographic negatives donated to their institution by the Boston Globe. Their work illuminates the tremendous power of emerging computational methods to uncover more complete histories, but it also serves as a reminder that such tools should be used with caution.

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来源期刊

American Journalism COMMUNICATION-

CiteScore

0.30

自引率

0.00%

发文量

期刊介绍： American Journalism, the peer-reviewed, quarterly journal of the American Journalism Historians Association, publishes original articles on the history of journalism, media, and mass communication in the United States and internationally. The journal also features historiographical and methodological essays, book reviews, and digital media reviews.