id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-344417-1seb8b09	Wang, Yuhang	SemSeq4FD: Integrating global semantic relationship and local sequential order to enhance text representation for fake news detection	2020-10-03		.txt	text/plain	8230	540	57	In this paper, we propose a novel graph-based neural network model named SemSeq4FD for early fake news detection based on enhanced text representations. Then a LSTM-based network is used to model the sequence of enhanced sentence representations, yielding the final document representation for fake news detection. To obtain enhanced text representations for fake news detection, we especially take into account the content structure-both global semantic relationship and local sequential order among sentences in a news document. Finally, we feed the enhanced sentence representations into the LSTM-based network sequentially, and obtain the informative document representation by max-pooling, which is further used for fake news detection. RQ3 What is the effect of LSTM, which is used to model the global sequential order information in the process of learning entire document-level representations for improving the fake news detection performance?	./cache/cord-344417-1seb8b09.txt	./txt/cord-344417-1seb8b09.txt