BiverWordle: Visualizing Stock Market Sentiment with Financial Text Data and Trends
Authors: 
Lei Xia, Yi-Ping Gao, Le Lin, Yu-Xi Chen, Kang ZhangAuthors Info & Claims
Lei Xia, Yi-Ping Gao, Le Lin, Yu-Xi Chen, Kang ZhangAuthors Info & ClaimsArticle No.: 18, Pages 1 - 5
Abstract
While financial forums are increasingly significant in financial analysis, current visualization tools do not properly exploit their text data. To address this, we present BiverWordle, a novel tool that reveals the relationship between market sentiment and firm trends. BiverWordle integrates candlestick chart, ThemeRiver, and Wordle with text classification and sentiment analysis techniques to decode market dynamics from textual sources, such as shareholder opinions and firm announcements. With the application of a Voting model to the manually labeled data, we achieved an accuracy of approximately 64%. BiverWordle facilitates the extraction of shareholder insights from sparse comments and provides a visual method for historical stock trend analysis, which we validated with three distinct stock trends. Resources are accessible at https://github.com/Brian-Lei-XIA/BiverWordle.
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- BiverWordle: Visualizing Stock Market Sentiment with Financial Text Data and Trends
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September 2023
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Published: 20 October 2023
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VINCI 2023
VINCI 2023: The 16th International Symposium on Visual Information Communication and Interaction
September 22 - 24, 2023
Guangzhou, China
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