Proceedings of the Third Workshop on Economics and Natural Language Processing最新文献

The Global Banking Standards QA Dataset (GBS-QA) 全球银行标准质量保证数据集(GBS-QA)

Proceedings of the Third Workshop on Economics and Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.econlp-1.3

Kyung-Woo Sohn, Sunjae Kwon, Jaesik Choi

引用次数: 0

A Fine-Grained Annotated Corpus for Target-Based Opinion Analysis of Economic and Financial Narratives 基于目标的经济金融叙事观点分析的细粒度注释语料库

Proceedings of the Third Workshop on Economics and Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.econlp-1.1

Jiahui Hu, P. Paroubek

{"title":"A Fine-Grained Annotated Corpus for Target-Based Opinion Analysis of Economic and Financial Narratives","authors":"Jiahui Hu, P. Paroubek","doi":"10.18653/v1/2021.econlp-1.1","DOIUrl":"https://doi.org/10.18653/v1/2021.econlp-1.1","url":null,"abstract":"In this paper about aspect-based sentiment analysis (ABSA), we present the first version of a fine-grained annotated corpus for target-based opinion analysis (TBOA) to analyze economic activities or financial markets. We have annotated, at an intra-sentential level, a corpus of sentences extracted from documents representative of financial analysts’ most-read materials by considering how financial actors communicate about the evolution of event trends and analyze related publications (news, official communications, etc.). Since we focus on identifying the expressions of opinions related to the economy and financial markets, we annotated the sentences that contain at least one subjective expression about a domain-specific term. Candidate sentences for annotations were randomly chosen from texts of specialized press and professional information channels over a period ranging from 1986 to 2021. Our annotation scheme relies on various linguistic markers like domain-specific vocabulary, syntactic structures, and rhetorical relations to explicitly describe the author’s subjective stance. We investigated and evaluated the recourse to automatic pre-annotation with existing natural language processing technologies to alleviate the annotation workload. Our aim is to propose a corpus usable on the one hand as training material for the automatic detection of the opinions expressed on an extensive range of domain-specific aspects and on the other hand as a gold standard for evaluation TBOA. In this paper, we present our pre-annotation models and evaluations of their performance, introduce our annotation scheme and report on the main characteristics of our corpus.","PeriodicalId":166554,"journal":{"name":"Proceedings of the Third Workshop on Economics and Natural Language Processing","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124516667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Cryptocurrency Day Trading and Framing Prediction in Microblog Discourse 微博话语中的加密货币日内交易与框架预测

Proceedings of the Third Workshop on Economics and Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.econlp-1.11

Anna Paula Pawlicka Maule, Kristen Marie Johnson

{"title":"Cryptocurrency Day Trading and Framing Prediction in Microblog Discourse","authors":"Anna Paula Pawlicka Maule, Kristen Marie Johnson","doi":"10.18653/v1/2021.econlp-1.11","DOIUrl":"https://doi.org/10.18653/v1/2021.econlp-1.11","url":null,"abstract":"With 56 million people actively trading and investing in cryptocurrency online and globally in 2020, there is an increasing need for automatic social media analysis tools to help understand trading discourse and behavior. In this work, we present a dual natural language modeling pipeline which leverages language and social network behaviors for the prediction of cryptocurrency day trading actions and their associated framing patterns. This pipeline first predicts if tweets can be used to guide day trading behavior, specifically if a cryptocurrency investor should buy, sell, or hold their cryptocurrencies in order to make a profit. Next, tweets are input to an unsupervised deep clustering approach to automatically detect trading framing patterns. Our contributions include the modeling pipeline for this novel task, a new Cryptocurrency Tweets Dataset compiled from influential accounts, and a Historical Price Dataset. Our experiments show that our approach achieves an 88.78% accuracy for day trading behavior prediction and reveals framing fluctuations prior to and during the COVID-19 pandemic that could be used to guide investment actions.","PeriodicalId":166554,"journal":{"name":"Proceedings of the Third Workshop on Economics and Natural Language Processing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114693420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

To What Extent Can English-as-a-Second Language Learners Read Economic News Texts? 英语作为第二语言的学习者能在多大程度上阅读经济新闻文本?

Proceedings of the Third Workshop on Economics and Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.econlp-1.9

Yo Ehara

引用次数: 0

Corporate Bankruptcy Prediction with Domain-Adapted BERT 基于领域适应BERT的企业破产预测

Proceedings of the Third Workshop on Economics and Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.econlp-1.4

Alex G. Kim, Sang-Yeong Yoon

引用次数: 4

Using Word Embedding to Reveal Monetary Policy Explanation Changes 用词嵌入揭示货币政策解释变化

Proceedings of the Third Workshop on Economics and Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.econlp-1.8

Akira Matsui, Xiang Ren, Emilio Ferrara

引用次数: 2

From Stock Prediction to Financial Relevance: Repurposing Attention Weights to Assess News Relevance Without Manual Annotations 从股票预测到财务相关性:重新利用注意力权重来评估没有手动注释的新闻相关性

Proceedings of the Third Workshop on Economics and Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.econlp-1.6

Luciano Del Corro, Johannes Hoffart

引用次数: 1

Extracting Economic Signals from Central Bank Speeches 从央行讲话中提取经济信号

Proceedings of the Third Workshop on Economics and Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.econlp-1.12

M. Ahrens, Michael McMahon

{"title":"Extracting Economic Signals from Central Bank Speeches","authors":"M. Ahrens, Michael McMahon","doi":"10.18653/v1/2021.econlp-1.12","DOIUrl":"https://doi.org/10.18653/v1/2021.econlp-1.12","url":null,"abstract":"Estimating the effects of monetary policy is one of the fundamental research questions in monetary economics. Many economies are facing ultra-low interest rate environments ever since the global financial crisis of 2007-9. The Covid pandemic recently reinforced this situation. In the US and Europe, interest rates are close to (or even below) zero, which limits the scope of traditional monetary policy measures for central banks. Dedicated central bank communication has hence become an increasingly important tool to steer and control market expectations these days. However, incorporating central bank language directly as features into economic models is still a very nascent research area. In particular, the content and effect of central bank speeches has been mostly neglected from monetary policy modelling so far. With our paper, we aim to provide to the research community a novel, monetary policy shock series based on central bank speeches. We use a supervised topic modeling approach that can deal with text as well as numeric covariates to estimate a monetary policy signal dispersion index along three key economic dimensions: GDP, CPI and unemployment. This “dispersion shock” series is not only more frequent than series that classically focus on policy announcement dates, it also opens up the possibility of answering new questions that have up until now been difficult to analyse. For example, do markets form different expectations when facing a “cacophony of policy voices”? Our initial findings for the US point towards the fact that more dispersed or incongruent monetary policy stance communication in the build up to Federal Open Market Committee (FOMC) meetings might be associated with stronger subsequent market surprises at FOMC policy announcement time.","PeriodicalId":166554,"journal":{"name":"Proceedings of the Third Workshop on Economics and Natural Language Processing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121057658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Is Domain Adaptation Worth Your Investment? Comparing BERT and FinBERT on Financial Tasks 领域适应值得你投资吗?比较BERT和FinBERT的财务任务

Proceedings of the Third Workshop on Economics and Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.econlp-1.5

Bo Peng, Emmanuele Chersoni, Yu-Yin Hsu, Chu-Ren Huang

引用次数: 19