Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/42368

TitleSentiment analysis of stock market behavior from Twitter using the R Tool
Author(s)Oliveira, Nuno
Cortez, Paulo
Areal, Nelson
Issue date2016
PublisherCRC Press
Abstract(s)Sentiment analysis is a hot research topic with widespread applications in organizations. Recently, it has been applied to create investor sentiment indicators that can be utilized in the prediction of stock market variables such as returns, volatility and trading volume. This chapter presents a use case about sentiment analysis in tweets related to stock mar- ket using the open-source R tool. We provide and explain code for the execution of diverse tasks, such as tweets collection, preprocessing tasks, utilization of opinion lexicons, application of machine learning (ML) methods, and respective evaluation. A data set composed by stock market tweets is also provided. This use case shows that the utilization of ML techniques using manually classified training data outperforms some standard sentiment word lists when applied to test data.
TypeBook part
URIhttp://hdl.handle.net/1822/42368
ISBN978-1-4822-3758-0
Publisher versionhttp://www.crcnetbase.com/isbn/9781482237580
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Livros e capítulos de livros/Books and book chapters

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