CLSIMay 5, 2020

Fine-grained Financial Opinion Mining: A Survey and Research Agenda

arXiv:2005.01897v3
AI Analysis

It identifies a gap in financial opinion mining for researchers and practitioners, but is incremental as it builds on existing work without presenting new results.

This paper addresses the lack of fine-grained analysis in financial opinion mining, which has traditionally focused on coarse-grained sentiment classification, by defining financial opinions and proposing a research agenda for future studies.

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 on 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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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