Identifying and Following Expert Investors in Stock Microblogs

By Roy Bar-Haim, Elad Dinur, Ronen Feldman, Moshe Fresko, Guy Goldstein. 2011

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Semantic Frames to Predict Stock Price Movement (2013, background): “…NLP techniques to various ﬁnancial media (conventional news, tweets) to detect sentiment in conventional news (Devitt and Ahmad, 2007; Haider and Mehrotra, 2011) or message boards (Chua et al., 2009), or discriminate expert from non-expert investors in ﬁnancial tweets (Bar-Haim et al., 2011).”
On the Importance of Text Analysis for Stock Price Prediction (2014, methodology): “(2013) introduced tree representations of information in news, Bollen et al. (2010) used Twitter data, Bar-Haim et al.”
Sentiment analysis: A review and comparative analysis of web services (2015, background): “well as other organizations such as governments, desire to know what people say about their marques, products or members [51,89,15,54,7,28,14,11,59].”
Sentiment Analysis and Opinion Mining (2012, unknown): “In Bar-Haim et al. (2011) and Feldman et al.”
A New Model for Stock Price Movements Prediction Using Deep Neural Network (2017, methodology): “Many new methods have been proposed to explore additional information (mainly online text data) for the stock forecasting such as ﬁnancial news [9, 26], twitters sentiments [23], micro blogs [3].”