Media-aware quantitative trading based on public Web information

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Improving stock market prediction via heterogeneous information fusion (2017, background): “News sentiments are measured and the combined eﬀect of Web news and social media on stock markets are studied in [29] .”
Tensor-Based Learning for Predicting Stock Movements (2015, unknown): “The common strategy in previous studies (Lavrenko et al. 2000; Li et al. 2014a; Mittermayer and Knolmayer 2006; Schumaker and Chen 2008; 2009b; Schumaker et al. 2012; Wang, Huang, and Wang 2011; Xu and Zhang 2013; Yu, Duan, and Cao 2013) is to concatenate features of different information sources in”
Natural language based financial forecasting: a survey (2017, methodology): “This theory was proposed by [60], and supported by empirical evidence from [102], [66], and [65].”
A Tensor-Based Information Framework for Predicting the Stock Market (2016, methodology): “Li et al. [2014a, 2014b] measured public sentiment by observing the interactive behaviors of investors on social media and studied the effect of ﬁrm-speciﬁc news on stock prices and public sentiment.”
Digital Finance and FinTech: current research and future research directions (2017, unknown): “Li et al. (2014) proposed a decision support system that takes into account sentiment expressed in stock communities during a 3-month period and also observed a good predictive performance.”