A Scaling Model for Estimating Time-Series Party Positions from Texts

@article{Slapin2007ASM,
  title={A Scaling Model for Estimating Time-Series Party Positions from Texts},
  author={Jonathan B. Slapin and Sven-Oliver Proksch},
  journal={American Journal of Political Science},
  year={2007},
  volume={52},
  pages={705-722}
}
However, existing text-based methods face challenges in producing valid and reliable time-series data. This article proposes a scaling algorithm called WORDFISH to estimate policy positions based on word frequencies in texts. The technique allows researchers to locate parties in one or multiple elections. We demonstrate the algorithm by estimating the positions of German political parties from 1990 to 2005 using word frequencies in party manifestos. The extracted positions reflect changes in… 

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References

SHOWING 1-10 OF 59 REFERENCES
Extracting Policy Positions from Political Texts Using Words as Data
We present a new way of extracting policy positions from political texts that treats texts not as discourses to be understood and interpreted but rather, as data in the form of words. We compare this
A Robust Transformation Procedure for Interpreting Political Text
TLDR
This note addresses several shortcomings in the transformation procedure introduced in the original Wordscores program, and demonstrates that the original transformation distorts the metric on which content scores are placed.
Left Right Political Scales - Some Expert Judgments
nations, usually measured in terms ‘of some more or less explicit Left-Right ideological scale. The need for such classification is quite apparent in the plethora of studies attempting to evaluate
Estimating the Policy Position of Political Actors
This book gives an up to date reference on the state of the art in this highly important methodological area, which is central both to theoretical models of party competition and to empirical
Expert Interpretations of Party Space and Party Locations in 42 Societies
The terms `left' and `right' are widely used to organize party competition and to shape connections between citizens and political parties. Recent and dramatic changes in the world, however, raise
Benchmarks for text analysis: A response to Budge and Pennings
Measuring Bias and Uncertainty in Ideal Point Estimates via the Parametric Bootstrap
Over the last 15 years a large amount of scholarship in legislative politics has used NOMINATE or other similar methods to construct measures of legislators' ideological locations. These measures are
Party Policy in Modern Democracies
Introduction Part I. Policy and Party Competition 1. Policy dimensions and political preferences 2. "Policy spaces" and models of party competition Part II. Measuring Policy Positions 3. The expert
A comparison of event models for naive bayes text classification
TLDR
It is found that the multi-variate Bernoulli performs well with small vocabulary sizes, but that the multinomial performs usually performs even better at larger vocabulary sizes--providing on average a 27% reduction in error over the multi -variateBernoulli model at any vocabulary size.
...
...