Post-Object Fandom: Television, Identity and Self-narrative
Author: Rebecca Williams
ISBN: 9781501319983
Book Cover Type:
Fandom is generally viewed as an integral part of everyday life which impacts upon how we form emotional bonds with ourselves and others in a modern, mediated world. Whilst it is inevitable for television series to draw to a close, the reactions of fans have rarely been considered. Williams explores this everyday occurence through close analysis of television fans to examine how they respond to, discuss, and work through their feelings when shows finish airing. Through a range of case studies, including The West Wing (NBC, 2000-2006), Lost (ABC 2004 -2010), Buffy the Vampire Slayer (1997-2003), Doctor Who (BBC 1963-1989; 2005-), The X-Files (FOX, 1993-2002), Firefly (FOX, 2002) and Sex and the City (HBO, 1998-2004), Williams considers how fans prepare for the final episodes of shows, how they talk about this experience with fellow fans, and how, through re-viewing, discussion and other fan practices, they seek to maintain their fandom after the show's cessation.
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HUMAN FRONTIERS: THE FUTURE OF BIG IDEAS IN AN AGE OF SMALL THINKING
I found this book very very helping for understanding basic concepts of maths; geometry;algebra; fractions; decimals; percentage; polygons and much more; I suggest or even request parents to buy this book for their childrens to be come conceptual students.
All countries, capitals and flags of the world: A guide to flags from around the world
Really liked it but please also bring other books such as The Pentagon's Brain DARPA by Annie Jacobsen and Rise and Kill First by Ronen Bergman
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30 Days of Creativity: Draw, Colour and Discover Your Creative Self
Philosophycally written and well researched book about most mysterious subject in neuro science
My interest in data science, machine learning and AI brought me to Pak Manifesto's website. This is a great book (and although I haven't read all of it) it basically underlines the importance of having a deep intuitive understanding of probability and being able to glean information from minute details in order to fine-tune one's predictions (about anything). The data on which such predictions are based, it quantity, breadth, depth and quality are all important, as is the broader canvas of knowledge surrounding the problem at hand.
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This book is a must read for any statistics and/or data science student or even a professional. Highly recommended from my side!
