Fr. 70.00

Data and Doctor Doom - An Empirical Approach To Transmedia Characters

Inglese · Tascabile

Spedizione di solito entro 6 a 7 settimane

Descrizione

Ulteriori informazioni

This book defines a straightforward way to analyse fictional characters through data. It shows how a data-led approach can produce rich analyses of characters, their surrounding storyworlds, and their authors across time and different types of media. It uses the Marvel Comics' character, Doctor Doom as its main case study, and demonstrates the advantages of this approach by comparing the results to those taken from a survey of fan attitudes. It also uses the methodology to analyse the differences between the American and British characters who share the name "Dennis The Menace". Finally, it offers a range of further uses for the tool. All datasets and tools are made available to download, so that other researchers can use the methodology and compare their own results to those generated in the book.

Sommario

1.Introduction.- 2. Methodology.- 3.The corpus and sample.- 4.Analysis.- 5.A Tale Of Two Menaces.- 6.Discussion.- Bibliography.- Appendix One: Using the unified model of transmedia character coherence.- Appendix Two: Doctor Doom Corpus.- Appendix Three: Example of signifier survey.

Info autore

Mark Hibbett is head of research information systems at University of the Arts London, UK. He has spent thirty years working with research data in arts and science contexts and his current research focuses on transmedia character cohesion, particularly related to superheroes and children's humour comics.

Dettagli sul prodotto

Autori Mark Hibbett
Editore Springer, Berlin
 
Lingue Inglese
Formato Tascabile
Pubblicazione 15.02.2025
 
EAN 9783031451751
ISBN 978-3-0-3145175-1
Pagine 302
Dimensioni 155 mm x 17 mm x 235 mm
Peso 488 g
Illustrazioni XVI, 302 p. 65 illus., 45 illus. in color.
Serie Palgrave Studies in Comics and Graphic Novels
Categorie Scienze sociali, diritto, economia > Sociologia > Altro

Populäre Kultur, Comics, Marvel, Popular Culture, Data, characters, Attitudes, Graphic Novel / Comic / Manga / Cartoon, Comics Studies

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