Predicting Partisan Responsiveness: A Probabilistic Text Mining Time-Series Approach
@article{Butkov2019PredictingPR, title={Predicting Partisan Responsiveness: A Probabilistic Text Mining Time-Series Approach}, author={Lenka Bu{\vs}t{\'i}kov{\'a} and David S. Siroky and Saud Alashri and Sultan Saeed Alzahrani}, journal={Political Analysis}, year={2019}, volume={28}, pages={47 - 64} }
When do parties respond to their political rivals and when do they ignore them? This article presents a new computational framework to detect, analyze and predict partisan responsiveness by showing when parties on opposite poles of the political spectrum react to each other’s agendas and thereby contribute to polarization. Once spikes in responsiveness are detected and categorized using latent Dirichlet allocation, we utilize the terms that comprise the topics, together with a gradient descent…
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