BiverWordle: Visualizing Stock Market Sentiment with Financial Text Data and Trends

doi:10.1145/3615522.3615541

科研成果详情

题名	BiverWordle: Visualizing Stock Market Sentiment with Financial Text Data and Trends
作者	Xia，Lei 1; Gao，Yi Ping 1; Lin，Le 1; Chen，Yu Xi 1; Zhang，Kang 2
发表日期	2023-09-22
会议录名称	ACM International Conference Proceeding Series
摘要	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.
关键词	Financial Text Processing Sentiment Analysis Visualization
DOI	10.1145/3615522.3615541
URL	查看来源
语种	英语English
Scopus入藏号	2-s2.0-85178381174
引用统计
文献类型	会议论文
条目标识符	https://repository.uic.edu.cn/handle/39GCC9TT/11570
专题	北师香港浸会大学
作者单位	1.Department of Computer Science,Beijing Normal University,Hong Kong Baptist University,United International College,Zhuhai,China,China 2.Computational Media and Arts,Hong Kong University of Science and Technology,Guangzhou,China
第一作者单位	北师香港浸会大学
推荐引用方式 GB/T 7714	Xia，Lei,Gao，Yi Ping,Lin，Leet al. BiverWordle: Visualizing Stock Market Sentiment with Financial Text Data and Trends[C], 2023.