DocumentCode :
229085
Title :
Movie analytics: Visualization of the co-starring network
Author :
Haughton, Dominique ; McLaughlin, Mark-David ; Mentzer, Kevin ; Changan Zhang
Author_Institution :
Bentley Univ., Paris, France
fYear :
2014
fDate :
9-10 Nov. 2014
Firstpage :
115
Lastpage :
116
Abstract :
This poster contributes a novel application of social network visualization techniques to the motion picture industry. We make the case and illustrate with examples that a visualization approach based on k-cores helps alleviate otherwise inextricable memory issues in analyses of the IMDb co-starring network, which contains more than 2.6 million actors displaying over a billion links, with degrees which can rise to about 50,000 and above for the most connected actors.
Keywords :
cinematography; entertainment; network theory (graphs); social networking (online); IMDb co-starring network analysis; co-starring network visualization; inextricable memory issues; k-cores; motion picture industry; movie analytics; social network visualization techniques; visualization approach; Color; Data visualization; Educational institutions; Indexes; Motion pictures; Visual databases; Visualization; IMDb; Movie Analytics; k-core decomposition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Large Data Analysis and Visualization (LDAV), 2014 IEEE 4th Symposium on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/LDAV.2014.7013216
Filename :
7013216
Link To Document :
بازگشت