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Automatic image tagging for corpus linguistics : a multimodal study of news representations of Islam / Paul Baker, Hanna Schmück, Yufang Qian.
Author
Baker, Paul, 1972-
[Browse]
Format
Book
Language
English
Published/Created
Cambridge : Cambridge University Press, 2025.
Description
1 online resource (81 pages) : digital, PDF file(s).
Details
Subject(s)
Corpora (Linguistics)
—
Data processing
—
Great Britain
[Browse]
Journalism, Pictorial
—
Great Britain
—
Data processing
[Browse]
Islam in mass media
—
Data processing
[Browse]
Muslims
—
Press coverage
—
Great Britain
[Browse]
Author
Schmück, Hanna
[Browse]
Qian, Yufang, 1965-
[Browse]
Series
Cambridge elements. Elements in corpus linguistics
[More in this series]
Cambridge elements. Elements in corpus linguistics, 2632-8097
[More in this series]
Restrictions note
Open Access.
Summary note
This Element reports on the creation and analysis of a 1.5-million-word corpus consisting of a year's worth of UK national press news articles about Islam and Muslims, published between December 2022 and November 2023. The corpus also contains 8,546 image files which have been automatically tagged using Google's Vertex AI. Analysis was carried out on three levels a) written text only, b) images only, c) interactions between written text and images. Using examples from the analyses, the authors demonstrate the affordances of these three approaches, providing a critical evaluation of Vertex AI's capabilities and the abilities of popular corpus software to work with visually tagged corpora. The Element acts as a practical guide for researchers who want to carry out this form of analysis. This title is also available as Open Access on Cambridge Core.
Notes
Title from publisher's bibliographic system (viewed on 18 Jul 2025).
ISBN
9781009581233 (ebook)
Statement on responsible collection description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
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