2023
DOI: 10.48550/arxiv.2301.09279
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StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time Series

Abstract: There has been growing interest in applying NLP techniques in the financial domain, however, resources are extremely limited. This paper introduces StockEmotions, a new dataset for detecting emotions in the stock market that consists of 10k English comments collected from StockTwits, a financial social media platform. Inspired by behavioral finance, it proposes 12 fine-grained emotion classes that span the roller coaster of investor emotion. Unlike existing financial sentiment datasets, StockEmotions presents … Show more

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“…The setup introduces features that contain sentiment scores extracted from news and a relevant online forum, as well as other stock-related historical information such as the opening, closing, highest, and lowest prices. In [26], a new dataset for stock market emotion detection is presented. The set contains data consisting of 12 fine-grained emotion classes concerning investor emotion.…”
Section: Related Workmentioning
confidence: 99%
“…The setup introduces features that contain sentiment scores extracted from news and a relevant online forum, as well as other stock-related historical information such as the opening, closing, highest, and lowest prices. In [26], a new dataset for stock market emotion detection is presented. The set contains data consisting of 12 fine-grained emotion classes concerning investor emotion.…”
Section: Related Workmentioning
confidence: 99%