Videos

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Understanding History through Topic Modeling Thumbnail

Understanding History through Topic Modeling

Presenter
  • David Blei
May 25, 2016
IPAM
Modeling Racial Segregation in the US Literary Field, 1880-1990 (with Richard Jean So) Thumbnail

Modeling Racial Segregation in the US Literary Field, 1880-1990 (with Richard Jean So)

Presenter
  • Hoyt Long
May 25, 2016
IPAM
The Algorithm and the Urn Thumbnail

The Algorithm and the Urn

Presenter
  • Lisa Rhody
May 24, 2016
IPAM
Abstract models for citable analyses of citable texts Thumbnail

Abstract models for citable analyses of citable texts

Presenter
  • David Smith
May 24, 2016
IPAM
Bayesian Poisson Tensor Decomposition for International Relations Thumbnail

Bayesian Poisson Tensor Decomposition for International Relations

Presenter
  • Hanna Wallach
May 24, 2016
IPAM
Natural Language Processing for Framing Thumbnail

Natural Language Processing for Framing

Presenter
  • Noah Smith
May 24, 2016
IPAM
The minor fall, the major lift: what can we learn from a large corpus of lyrics? Thumbnail

The minor fall, the major lift: what can we learn from a large corpus of lyrics?

Presenter
  • Yong-Yeol Ahn
May 23, 2016
IPAM
Sentiment Analysis as Proxy for Plot Thumbnail

Sentiment Analysis as Proxy for Plot

Presenter
  • Matthew Jockers
May 23, 2016
IPAM
Inferring Network Structure from Textual Evidence Thumbnail

Inferring Network Structure from Textual Evidence

Presenter
  • David Smith
May 23, 2016
IPAM
The Language of Food Thumbnail

The Language of Food

Presenter
  • Dan Jurafsky
May 23, 2016
IPAM
Do happy people get more from their friends?: What we can learn about social networks from text analysis Thumbnail

Do happy people get more from their friends?: What we can learn about social networks from text analysis

Presenter
  • Kristina Lerman
May 23, 2016
IPAM
Mining personal names in the ‘Big Data’ to map Diasporas Thumbnail

Mining personal names in the ‘Big Data’ to map Diasporas

Presenter
  • Elian Carsenat
May 18, 2016
IPAM