Determining the Function of Political Tweets

We study the discursive practices of politicians and journalists on social media. For this we need more annotated data than we currently have but the annotation process is time-consuming and costly. In this paper we examine machine learning methods for automatically annotating unseen tweetsbased on a small set of manually annotated tweets. Forimproving the performance of the learner, we focus onmethods related to training data expansion, like artificialtraining data, active learning and incorporating languagemodels developed from unannotated text

Active Learning for Classifying Political Tweets

We examine methods for improving models for automatically labeling social media data. In particular we evaluate active learning: a method for selecting candidate training data whose labeling the classification model would benefit most of. We show that this approach requires careful ex-periment design, when it is combined with language modelin