id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-313183-4zmtijyo	Li, Jianping	Tourism companies' risk exposures on text disclosure	2020-06-29		.txt	text/plain	8215	465	52	Penela and Serrasqueiro (2019) recognized the importance of risk identification for lodging companies and introduced textual risk disclosure data in Form 10-K, which have been proved to be a feasible and effective data source to evaluate company risk exposure into the tourism sector (Bao & Datta, 2014; Campbell et al., 2014; Wei, Li, Li, & Zhu (2019) ; Wei et al., 2019c) . To this end, we introduce the Sentence Latent Dirichlet Allocation (Sent-LDA) model, which is an unsupervised clustering method that can effectively identify hidden knowledge from a large amount of text to analyze the textual risk disclosure data in Forms 10-K by all listed tourism companies during 2006-2019. To identify the risk exposures disclosed in financial statements of tourism companies, this paper applies a topic model named Sentence Latent Dirichlet Allocation (Sent-LDA) proposed by Bao and Datta (2014) , which is an extension of the original Latent Dirichlet Allocation model (LDA).	./cache/cord-313183-4zmtijyo.txt	./txt/cord-313183-4zmtijyo.txt