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Sentiment analysis-based prediction of -meme stock- price movements
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Resumo(s)
This paper investigates the relation of daily twitter sentiment to the
stock prices of two portfolios for a three-year time-period, one
consisting of popular meme stocks, the other of NASDAQ stocks.
The objective is to detect differences in the behavior of both
portfolios in this relation. In its sentiment classification, the paper
makes use of Textblob, customized VADER, roBERTa as well as
a manually trained GRU neural network while relying on classic
binary classifiers to predict price movements. The results indicate
a stronger predictability for the NASDAQ portfolio, most likely
due to issues of information quality.
Descrição
Palavras-chave
Sentiment Aanalysis Meme stocks Twitter