An Active Learning Framework for Classifying Political Text

@inproceedings{Hillard2007AnAL,
  title={An Active Learning Framework for Classifying Political Text},
  author={Dustin Hillard and Stephen Purpura and John Wilkerson and Bryan Jones and Frank P. Baumgartner and Richard J Zeckhauser and Jesse Shapiro and Claire Cardie and Eduard H. Hovy and David Lazer and Michael Neblo and Kevin M. Esterling and Aleks Jakulin and Matthew Baum and Jamie Callan and Micah Altman and David King and James E. Purpura and A. I. Gibson and Julianna Rigg and Wilkerson Hillard},
  year={2007}
}
We develop a framework and tools for applying a computer‐assisted context analysis system and find that it achieves levels of accuracy comparable to humans for about 80% less effort when starting from scratch (no labeled examples). The system is presented using a case study of Congressional bill titles as a proxy for the full text of Congressional bills. We also demonstrate that the system can use information learned from previous experiments to reduce the labeling requirements still further to… CONTINUE READING
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