A Research Agenda for Financial Opinion Mining

Authors

  • Chung-Chi Chen Department of Computer Science and Information Engineering, National Taiwan University, Taiwan
  • Hen-Hsen Huang Department of Computer Science, National Chengchi University, Taiwan MOST Joint Research Center for AI Technology and All Vista Healthcare, Taiwan
  • Hsin-Hsi Chen Department of Computer Science and Information Engineering, National Taiwan University, Taiwan MOST Joint Research Center for AI Technology and All Vista Healthcare, Taiwan

Keywords:

Measuring predictability of real world phenomena based on social media, e.g., spanning politics, finance, and health, Subjectivity in textual data; sentiment analysis; polarity/opinion identification and extraction, linguistic analyses of social media behavior, Trend identification and tracking; time series forecasting, Credibility of online content

Abstract

Opinion mining is a prevalent research issue in many domains. In the financial domain, however, it is still in the early stages. Most of the researches on this topic only focus on the coarse-grained market sentiment analysis, i.e., 2-way classification for bullish/bearish. Thanks to the recent financial technology (FinTech) development, some interdisciplinary researchers start to involve in the in-depth analysis of investors' opinions. In this position paper, we first define the financial opinions from both coarse-grained and fine-grained points of views, and then provide an overview of the issues already tackled. In addition to listing research issues of the existing topics, we further propose a road map of fine-grained financial opinion mining for future researches, and point out several challenges yet to explore. Moreover, we provide possible directions to deal with the proposed research issues.

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Published

2021-05-22

How to Cite

Chen, C.-C., Huang, H.-H., & Chen, H.-H. (2021). A Research Agenda for Financial Opinion Mining. Proceedings of the International AAAI Conference on Web and Social Media, 15(1), 1059-1063. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/18130