Tweets and Trades: The Information Content of Stock Microblogs

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Identifying and Following Expert Investors in Stock Microblogs (2011, methodology): “Messages were classiﬁed by matching positive and negative terms from sentiment lexicons, learning from a hand-labeled set of messages, or some combination of the two (Das and Chen, 2007; Antweiler and Frank, 2004; Chua et al., 2009; Zhang and Skiena, 2010; Sprenger and Welpe, 2010).”
Analyzing Stock Market Movements Using Twitter Sentiment Analysis (2012, background): “1% which is significantly less than previous research [11], [7].”
Intraday online investor sentiment and return patterns in the U.S. stock market (2017, methodology): “…literature that examines new data from the Internet to forecast stock markets (see, among others, Da et al. (2015), Moat et al. (2013), Avery et al. (2016), Chen et al. (2014), and Sprenger et al. (2014a)) by focusing on user-generated content published on the social media platform StockTwits.”
Social Media Sentiment in International Stock Returns and Trading Activity (2020, methodology): “Mentioning, retweeting, and following mechanisms are important for microblogging sites for which tracking information diffusion is possible (Sprenger et al. 2014).”