Ninth Annual Conference on New Directions in Analyzing Text as Data (TADA 2018): Program

Submitted by nasmith@washin… on Tue, 09/04/2018 - 10:51

Sponsors

Notes

 

Friday, September 21

 

8:00am - 9:00am:  Breakfast

9:00am - 9:15am:  Welcome

9:15am - 10:30am:  Topics

  • Toward Practical and Locally Private Inference of Topic Models
    Alexandra Schofield, Aaron Schein, Zhiwei Steven Wu, Mingyuan Zhou, and Hanna Wallach
  • Finding Meaning in Text: Fitting and Validating Anchored Topic Models
    Patrick van Kessel and Adam Hughes
  • A Robust Latent Dirichlet Allocation Approach for the Study of Political Text
    Andreu Casas, Tianyi Bi, and John Wilkerson
  • Discussants:  Burt Monroe and Margaret Roberts

10:30am - 10:45am:  Coffee break

10:45am - 12:00pm:  Uncertainty

  • Text Analysis of Text Analysis Syllabi
    Fréchet Nadjim and Yannick Dufresne
  • Measuring Uncertainty in Social Science Texts
    Sarah Bouchat
  • The Least Unclear Language: How Avoiding Negatives Produces Positive Understanding
    Christian Mueller and Tom Paskhalis
  • Discussants:  Amber Boydstun and Graeme Hirst

12:00pm - 1:30pm:  Lunch, courtesy of our platinum sponsor Microsoft Research, and doctoral consortium mentoring conversations

1:30pm - 2:45pm:  Well, Actually

  • Mansplaining the Law: The Effect of Gender, Ideology and Seniority at Congressional Hearings
    Michael Miller and Joseph Sutherland
  • Implicit Bias in Judicial Language
    Elliott Ash, Daniel Chen, and Arianna Ornaghi
  • Is Your Representative a Grandstander? Measuring Message Politics in Committee Hearings
    Ju Yeon (Julia) Park
  • Discussants:  David Mimno and Cheryl Schonhardt-Bailey

2:45pm - 3:15pm:  Break (please exit the room)

3:15pm - 3:30pm:  Poster setup for doctoral consortium presenters

3:30pm - 5:30pm:  Doctoral consortium poster session (including food and drinks)

6:00pm - 9:00pm:  Party at the Agua Verde Waterfront Garden Pavilion (more food and drinks)

 

Saturday, September 22

8:00am - 9:15am:  Breakfast

9:15am - 10:30am:  Decisions

  • Deep Voting: Measuring Ideology and Predicting Votes from Bill Texts using Neural Networks
    Nick Beauchamp and Alex Herzog
  • Mining Human Decision Making
    Margaret Roberts and Luke Sanford
  • Topic Selection in Conversation
    Michael Yeomans and Alison Wood Brooks
  • Discussants:  Cecilia Aragon and Bryce Dietrich

10:30am - 10:45am:  Coffee break

10:45am - 12:00pm:  Quotidian Text as Data

  • Political-ish: Comparing Political and Everyday Language on Social Media for Turnout and Election Forecasting
    William Hobbs, Lisa Friedland, Kenneth Joseph, Stefan Wojcik, and David Lazer
  • Boring in a New Way: Estimation and Inference for Political Style at Westminster, 1935–2018
    Arthur Spirling, Leslie Huang, and Patrick Perry
  • Pronoun Usage as a Measure of Power Personalization: A General Theory with Evidence from the Chinese-Speaking World
    Amy H. Liu
  • Discussants:  Jacob Eisenstein and Jacob Montgomery

12:00pm:  Lunch, courtesy of our platinum sponsor Microsoft Research

12:30pm - 1:15pm:  Roundtable conversation on diversity in text-as-data research

1:30pm - 2:45pm:  New Directions in Comparing Text as Data

  • Matching with Text Data: An Experimental Evaluation of Methods for Matching Documents and of Measuring Match Quality
    Reagan Mozer, Luke Miratrix, Aaron Russell Kaufman, and L. Jason Anastasopoulos
  • Word Shift: A General Method for Visualizing and Explaining Pairwise Comparisons Between Texts
    Ryan J. Gallagher, Andrew J. Reagan, Morgan R. Frank, Christopher M. Danforth, Peter Sheridan Dodds
  • Analysis of Political Texts in Multiple Languages
    Mitchell L. Goist and Burt L. Monroe
  • Discussants:  Amy Liu and Brandon Stewart

3:00pm - 4:00pm:  Closing discussion