Financial Opinion Mining (2021)

Abstract: In this tutorial, we will show where we are and where we will be to those researchers interested in this topic. We divide this tutorial into three parts, including coarse-grained financial opinion mining, fine-grained financial opinion mining, and possible research directions. This tutorial starts by introducing the components in a financial opinion proposed in our research agenda and summarizes their related studies. We also highlight the task of mining customers’ opinions toward financial services in the FinTech industry, and compare them with usual opinions. Several potential research questions will be addressed. We hope the audiences of this tutorial will gain an overview of financial opinion mining and figure out their research directions.

## goal of the tutorial when it comes to financial opinion mining, bullish and bearish come into people's minds. however, more fine-grained information will be missed if we only focus on the market sentiment analysis of financial documents. thanks to the recent "cs + x" trend, more interdisciplinary cooperation exists between computer science and other domains. in the "nlp + finance" community, lots of recent works pay their attention to in-depth analysis of different kinds of financial documents rather than market sentiment prediction. for example, our previous works @xcite find that the numeral information extracted from financial social media data is comparable to the price targets extracted from professional analysts' reports. @xcite analyze the pragmatic and semantic features in the earnings conference calls and discuss how these features influence the investor's decision-making process. @xcite point out the difference between the textual factors and cognitive factors by comparing the accurate and inaccurate professional analysts' reports. the abovementioned works conclude the necessity of capturing fine-grained opinions in the financial narratives. as the increasing interest of our community on this topic, recently, more and more related workshops spring up in the leading conferences, including finweb-2021 in the web conference, finnlp-2021 in ijcai, finir-2020 in sigir, and fnp-2020 in coling. in this tutorial, we will show where we are and where we will be to those researchers interested in this topic. we divide this tutorial into three parts, including coarse-grained financial opinion mining, fine-grained financial opinion mining, and possible research directions. this tutorial starts by introducing the components in a financial opinion proposed in our research agenda @xcite and summarizes their related studies. we also highlight the task of mining customers' opinions toward financial services in the fintech industry, and compare them with usual opinions. several potential research questions will be addressed. the audiences of this tutorial will gain an overview of financial opinion mining and figure out their research directions. ## tutorial outline we will cover the following topics based on recent works published in representative conferences and workshops. both technical details and the application scenarios will be introduced. the contrast of financial opinion mining with general opinion mining will also be discussed. the characteristics of different kinds of financial documents will be listed. ## recommended small reading list we recommend the audiences to read the following papers, which will be discussed in the tutorial. keith and stent (2019) • for conceiving the proposed research directions: chen et al. (2021a) 5 presenters chung-chi chen 1 is currently a postdoctoral researcher at the most joint research center for ai technology and all vista healthcare, taiwan. he got the ph.d. degree in the department of computer science and information engineering at national taiwan university. he received the m.s. degree in quantitative finance from national tsing hua university, taiwan. his research focuses on opinion mining and sentiment analysis in finance. he is the organizer of finnum shared task series in ntcir (2018-2022) and the finnlp workshop series in ijcai (2019-2021). he is the presenter of the aacl-2020 "natural language processing in financial technology applications" tutorial and the presenter of the emnlp-2021 "financial opinion mining" tutorial. his work has been published in acl, www, sigir, ijcai, and cikm, and served as pc members in acl, aaai, emnlp, cikm, and wsdm. he won the 1st prize in both the jih sun fintech hackathon (2019) and the standard chartered fintech competition (2018), and the 2nd prize in both the jih sun fintech hackathon (2018) and the e.sun fhc fintech hackathon (2017). hen-hsen huang foot_1 is an assistant research fellow at the institue of information science, academia sinica, taiwan. his research interests include natural language processing and information retrieval. his work has been published in acl, si-gir, www, ijcai, cikm, coling, and so on. dr. huang received the honorable mention of doctoral dissertation award of aclclp in 2014 and the honorable mention of master thesis award of aclclp in 2008. he served as the registration chair of taai 2017, the publication chair of ro-cling 2020, and as pc members of representative conferences in computational linguistics including acl, coling, emnlp, and naacl. he was one of organizers of finnum task at ntcir and finnlp workshop at ijcai. hsin-hsi chen foot_2 received the ph.d. degree in electrical engineering in 1988 from national taiwan university, taipei, taiwan. since august 2018, hsin-hsi chen has been a distinguished professor in the department of computer science and information engineering, national taiwan university. he was conference chair of ijcnlp 2013, program co-chair of acm sigir 2010, senior pc members of acm sigir 2006, 2007, 2008 and 2009, area/track chairs of aaai 2020, emnlp 2018, acl 2012, acl-ijcnlp 2009 and acm cikm 2008, and pc members of many conferences (ijcai, sigir, wsdm, acl, coling, emnlp, naacl, eacl, ijcnlp, www, and so on). he will be conference chair of acm sigir 2023. he received google research awards in 2007 and 2012, most outstanding research award in 2017, and the amtran chair professorship in 2018.