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[EMNLP 2021 Tutorial] Financial Opinion Mining.pdfRelated Publications
Related Publications
From Opinion Mining to Financial Argument Mining. Open Access: Springer
Abstract: This book provides a foundation for newcomers to understand the challenges and methods in financial opinion mining and to indicate the road map for researchers to achieve professional-level financial opinion understanding. Because the financial market changes with the participants’ behaviors (e.g., buying or selling), the opinions of market participants become a crucial clue when analyzing the movement of financial instruments’ prices. In this book, we adopt the notions of argument mining for an in-depth analysis of the opinions of financial market participants. We first define financial opinion in terms of basic components, and then determine the structures within an opinion and among opinions. A survey shows where we are now with the introductions of both classical approaches in general opinion mining and the latest works in financial opinion mining. In particular, the recent advances in the deep learning approach have led to substantial progress in many areas of artificial intelligence such as NLP and FinTech. This book will cover the related cutting-edge technologies including numeracy understanding, argument mining and financial document processing. Several unexplored research questions and potential application scenarios are also presented in the research agenda, pointing out where we are going. We hope the insights of this book can inspire researchers in both academics and industry, and further prompt them to join the field of financial argument mining.Quickstart Guide
Evaluating the Rationales of Amateur Investors. Open Access: WWW
Abstract: Pilot explorations and a brief introduction to financial argument mining are shown in this paper.A Research Agenda for Financial Opinion Mining. Open Access: ICWSM
Abstract: A brief introduction of opinion mining in finance.Page updated
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