Natural language processing (NLP) techniques have been applied to extract information from company filings (Lee et al., 2014), financial news articles (Xie et al., 2013) and social media texts (Bollen et al., 2011) in order to gain understandings of financial markets.
traditional methods exploited statistical signals, such as lexical and syntactic features (Wang and Hua, 2014;Schumaker and Chen, 2009), sentiment (Bollen et al., 2011) and event structures (Ding et al., 2014;Ding et al., 2015;Ding et al., 2016) from these text sources, which suffers from feature sparsity problems.