A Research Agenda for Financial Opinion Mining
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
AbstractOpinion 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.
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. https://doi.org/10.1609/icwsm.v15i1.18130