Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/31273

TitleAutomatic creation of stock market lexicons for sentiment analysis using StockTwits data
Author(s)Oliveira, Nuno
Cortez, Paulo
Areal, Nelson
KeywordsSentiment analysis
Opinion mining
Stock market
Lexicon
Microblogging data
Information retrieval
Issue date2014
PublisherACM
Abstract(s)Sentiment analysis has been increasingly applied to the stock market domain. In particular, investor sentiment indicators can be used to model and predict stock market variables. In this context, the quality of the sentiment analysis is highly dependent of the opinion lexicon adopted. However, there is a lack of lexicons adjusted to microblogging stock market data. In this work, we propose an automatic procedure for the creation of such lexicon by exploring a large set of labeled messages from StockTwits, a popular financial microblogging service, and using four statistical measures: adaptations of the known TF-IDF, Information Gain, Class Percentage, and a newly proposed Weighted Class Probability. The obtained lexicons are competitive when compared with a set of six reference lexicons. Moreover, we verified that it is beneficial to use continuous sentiment scores instead of sentiment labels.
TypeConference paper
URIhttp://hdl.handle.net/1822/31273
ISBN978-1-4503-2627-8
DOI10.1145/2628194.2628235
Publisher versionThe original publication is available at http://dx.doi.org/10.1145/2628194.2628235
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings
EEG - Comunicações e Conferências

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