id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-175846-aguwenwo	Chatsiou, Kakia	Text Classification of Manifestos and COVID-19 Press Briefings using BERT and Convolutional Neural Networks	2020-10-20		.txt	text/plain	3188	192	47	We use manually annotated political manifestos as training data to train a local topic ConvolutionalNeural Network (CNN) classifier; then apply it to the COVID-19PressBriefings Corpus to automatically classify sentences in the test corpus.We report on a series of experiments with CNN trained on top of pre-trained embeddings for sentence-level classification tasks. To aid fellow scholars with the systematic study of such a large and dynamic set of unstructured data, we set out to employ a text categorization classifier trained on similar domains (like existing manually annotated sentences from political manifestos) and use it to classify press briefings about the pandemic in a more effective and scalable way.	./cache/cord-175846-aguwenwo.txt	./txt/cord-175846-aguwenwo.txt