Scientific Library of Tomsk State University

   E-catalog        

Normal view MARC view

Movie Analytics electronic resource A Hollywood Introduction to Big Data / by Dominique Haughton, Mark-David McLaughlin, Kevin Mentzer, Changan Zhang.

By: Haughton, Dominique [author.]Contributor(s): McLaughlin, Mark-David [author.] | Mentzer, Kevin [author.] | Zhang, Changan [author.] | SpringerLink (Online service)Material type: TextTextSeries: SpringerBriefs in StatisticsPublication details: Cham : Springer International Publishing : Imprint: Springer, 2015Description: VIII, 64 p. 53 illus., 45 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783319094267Subject(s): Statistics | Data mining | Computer graphics | Statistics | Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law | Data Mining and Knowledge Discovery | Computer GraphicsDDC classification: 519.5 LOC classification: QA276-280Online resources: Click here to access online
Contents:
What do we know about analyzing movie data: section on past literature.- What does "Big Data" mean; the data scientist point of view.- Visualization of very large networks: the co-starring social network.- Movie attendance and trends -- Oscar prediction and prediction markets -- Can we predict Oscars from Twitter and movie review data.
In: Springer eBooksSummary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
No physical items for this record

What do we know about analyzing movie data: section on past literature.- What does "Big Data" mean; the data scientist point of view.- Visualization of very large networks: the co-starring social network.- Movie attendance and trends -- Oscar prediction and prediction markets -- Can we predict Oscars from Twitter and movie review data.

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.

There are no comments on this title.

to post a comment.
Share