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.

Shows how a data-led approach can produce rich analyses of characters Uses the Marvel Comics character Doctor Doom as its main case study Analyses the differences between the American and British characters who share the name "Dennis The Menace"

Autorentext
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.

Klappentext

"The empirically grounded method presented here adds a truly innovative and much-needed tool to the growing field of transmedia character studies. I hope it will give rise to many further studies. But of course, Doom had to be first! Highly recommended for students as well as researchers."

• Stephan Packard , Professor of Popular Culture and Its Theories, University of Cologne, Germany

"A complete data-driven examination into what makes the universe's greatest supervillain tick. Read it now! Doom demands nothing less!"

• Ryan North , Author of Dinosaur Comics , The Unbeatable Squirrel Girl and The Fantastic Four

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.

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.

Inhalt

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.