David Bamman's guest appearances

David Bamman

NLP Highlights

Diaries of Social Data Research

Brendan O'Connor

Diyi Yang

Ines Montani

Noah Smith

Michael Collins

Brandon Stewart

Victor Sanh

Ethan Zuckerman

Sam Bowman

Nathan Schneider

Matt Gardner

Lauren Klein

Chris Dyer

John Hewitt

Dan Roth

OwlTail

Ted Underwood

This episode features Ted Underwood, a professor in the School of Information Sciences and Department of English at the University of Illinois Urbana-Champaign, and David Bamman, an associate professor at UC Berkeley’s School of Information. We discuss their 2018 Cultural Analytics paper co-authored with literary studies PhD student Sabrina Lee, titled “The Transformation of Gender in English-Language Fiction.” We trace how Twitter brought Ted and David together as collaborators, and the email that sparked the beginnings of this project. They describe how this paper uses predictive modeling for an unconventional purpose, and various “means of interrogating data.” They also provide tips for establishing collaborative relationships, and advocate using substantive research questions to motivate learning technical skills.

This episode features Ted Underwood, a professor in the School of Information Sciences and Department of English at the University of Illinois Urbana-Champaign, and David Bamman, an associate professor at UC Berkeley’s School of Information. We discuss their 2018 Cultural Analytics paper co-authored with literary studies PhD student Sabrina Lee, titled “The Transformation of Gender in English-Language Fiction.” We trace how Twitter brought Ted and David together as collaborators, and the email that sparked the beginnings of this project. They describe how this paper uses predictive modeling for an unconventional purpose, and various “means of interrogating data.” They also provide tips for establishing collaborative relationships, and advocate using substantive research questions to motivate learning technical skills.

18. Gender Patterns in English-Language Fiction and Interrogating Data with Ted Underwood and David Bamman

In this episode, we invite David Bamman to give an overview of computational humanities. We discuss examples of questions studied in computational humanities (e.g., characterizing fictionality, assessing novelty, measuring the attention given to male vs. female characters in the literature). We talk about the role NLP plays in addressing these questions and how the accuracy and biases of NLP models can influence the results. We also discuss understudied NLP tasks which can help us answer more questions in this domain such as literary scene coreference resolution and constructing a map of literature geography.David Bamman's homepage: http://people.ischool.berkeley.edu/~dbamman/LitBank dataset: https://github.com/dbamman/litbank

In this episode, we invite David Bamman to give an overview of computational humanities. We discuss examples of questions studied in computational humanities (e.g., characterizing fictionality, assessing novelty, measuring the attention given to male vs. female characters in the literature). We talk about the role NLP plays in addressing these questions and how the accuracy and biases of NLP models can influence the results. We also discuss understudied NLP tasks which can help us answer more questions in this domain such as literary scene coreference resolution and constructing a map of literature geography. David Bamman's homepage: <a href="http://people.ischool.berkeley.edu/~dbamman/" rel="nofollow" target="_blank">http://people.ischool.berkeley.edu/~dbamman/</a> LitBank dataset: <a href="https://github.com/dbamman/litbank" rel="nofollow" target="_blank">https://github.com/dbamman/litbank</a>

92 - Computational Humanities, with David Bamman