Back to Results
First PageMeta Content
Science / Computational linguistics / Social media / Statistical classification / Text messaging / Twitter / Topic model / Latent Dirichlet allocation / Unsupervised learning / Statistics / Statistical natural language processing / Machine learning


Interpreting Arts Audiences and Cultural Preference Through Twitter Data Shauna Concannon and Matthew Purver Queen Mary University of London Abstract. In this study we work with a multi-arts organ
Add to Reading List

Document Date: 2014-07-29 07:55:06


Open Document

File Size: 162,98 KB

Share Result on Facebook

City

London / Plymouth / /

Company

Latent Dirichlet Allocation LDA / Twitter / /

Country

Jordan / United Kingdom / Jamaica / /

/

EntertainmentAwardEvent

Dance Film Festival / Theatre / Music / Film and Festivals / /

Facility

Barbican Road / Matthew Purver Queen Mary University of London s.concannon@qmul.ac.uk Abstract / Barbican Centre / Hack The Barbican / /

IndustryTerm

month long technology / travel blogs / interpretable text mining / media art / natural language processing methods / malt beverage peach / /

Organization

San Francisco Film Centre / Barbican Centre / Arts and Humanities Research Council / Barbican / National Academy of Sciences / University of London / /

Person

Ryan Nelson / Anthony McCall / Liebling / Carlos Cruz-Diez / Shauna Concannon / /

Position

D.J. / /

PublishedMedium

Proceedings of the National Academy of Sciences / Journal of Machine Learning Research / /

Technology

natural language processing / automatic identification / month long technology / machine learning / /

SocialTag