07/06/2021

A Research Agenda for Financial Opinion Mining

Chung-Chi Chen, Hen-Hsen Huang, Hsin-Hsi Chen

Keywords: Credibility of online content, Subjectivity in textual data, sentiment analysis, polarity/opinion identification and extraction, linguistic analyses of social media behavior, Trend identification and tracking, time series forecasting, Measuring predictabil

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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