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Character Networks in Contemporary U.S. Fiction
A defining shift in 21st-century American culture has been the visibility of our social networks. Our vocabulary for understanding politics and culture is now saturated with terms describing patterns of positioning and group dynamics, such as jobseeker networking, reach, going viral, grassroots networks, and partisan bubbles.......
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A defining shift in 21st-century American culture has been the visibility of our social networks. Our vocabulary for understanding politics and culture is now saturated with terms describing patterns of positioning and group dynamics, such as jobseeker networking, reach, going viral, grassroots networks, and partisan bubbles. Contemporary novelists are shrewd observers of the "LinkedIn lunatics," "Columbuses," leakers, and others that reflect a shifting landscape of values in the network society. Character Networks in Contemporary U.S. Fiction reads this historical context alongside social network analysis and narrative theory, in order to argue that novelists, too, model complex social networks. To this end, Scott Selisker develops methods for illustrating and interpreting such "character networks," which comprise character groupings, go-betweens, unlikely encounters, and surprise realignments. Selisker reveals that many concepts in popular criticism, from the Bechdel test to sidekicks of color and manic pixie dream girls, describe characters in terms of their network positioning. Through readings of novels about WikiLeaks, cultural appropriation, and grassroots collectives, this book shows how novelists plot out the limited agency of their characters within carefully orchestrated social spheres. Building on recent work in theories of the novel and narrative, Selisker argues that putatively individual facets of literary character—roundness, privacy, authenticity, and agency—are best understood through the ways they are socially distributed, or networked.
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| Produktnavn | Character Networks in Contemporary U.S. Fiction |
| Merke | Other Brand |
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