TY - GEN digital ID - 131706555 TI - Movie Analytics : A Hollywood Introduction to Big Data AU - Haughton, Dominique AU - McLaughlin, Mark-David AU - Mentzer, Kevin AU - Zhang, Changan PY - 2015 SN - 9783319094267 9783319094250 9783319094274 PB - Cham Springer International Publishing DB - UniCat KW - Sociology KW - Statistical science KW - Law KW - Mathematical statistics KW - Information systems KW - Artificial intelligence. Robotics. Simulation. Graphics KW - datamining KW - grafische vormgeving KW - wetgeving KW - statistiek KW - data acquisition UR - https://www.unicat.be/uniCat?func=search&query=sysid:131706555 AB - Movies will never be the same after you learn how to analyze movie data, including key data mining, text mining and social network analytics concepts. These techniques may then be used in endless other contexts. In the movie application, this topic opens a lively discussion on the current developments in big data from a data science perspective. This book is geared to applied researchers and practitioners and is meant to be practical. The reader will take a hands-on approach, running text mining and social network analyses with software packages covered in the book. These include R, SAS, Knime, Pajek and Gephi. The nitty-gritty of how to build datasets needed for the various analyses will be discussed as well. This includes how to extract suitable Twitter data and create a co-starring network from the IMDB database given memory constraints. The authors also guide the reader through an analysis of movie attendance data via a realistic dataset from France. ER -