Digital By-Product Data in Web 2.0

Exploring Mass Collaboration of Wikipedia

Zeyi He (Autor)

Buch | Hardcover

275 Seiten

2013 | Unabridged edition
Cambridge Scholars Publishing (Verlag)
978-1-4438-4174-0 (ISBN)

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Thanks to Information and Communication Technologies (ICTs), every action on the Internet nowadays is recorded by digital by-product data: online purchases, tagging friends’ photos, browsing webpages, etc. This unprecedented technological revolution has empowered us with unique abilities to understand not only people’s behaviours, but also online platforms. Business corporates and academic researchers alike have both embarked on actively mining such information to stay ahead of the game in the digital age. Once lost in the sea of information that is present in every corner of the Internet, we now have a better appreciation of the beauty in this rich body of information aided by improved computing power. The deconvolution of the daily records provides us with a road map that leads us to explore who we are, what we did, what we want and why we want certain things, etc. This hidden source of information is beginning to surface, as is its potential in paving the way for us to better understand our society and ourselves.This book discusses the undiscovered opportunity of using digital by-product data, which is automatically generated from all internet applications for housekeeping functions. This book then continues to examine the possibility and operability for social scientists to conduct academic research of web 2.0 applications by analysing and visualizing digital by-product data.

Dr Zeyi He is currently working for the world’s top telecommunication company after obtaining her PhD from the University of York, UK, in 2012. Her research interests include a wide range of topics related to web2.0, ICTs, data mining, data visualization, and enterprise modeling.

Erscheint lt. Verlag	2.12.2013
Verlagsort	Newcastle upon Tyne
Sprache	englisch
Maße	148 x 212 mm
Themenwelt	Informatik ► Datenbanken ► Data Warehouse / Data Mining
ISBN-10	1-4438-4174-9 / 1443841749
ISBN-13	978-1-4438-4174-0 / 9781443841740
Zustand	Neuware