A Deep Learning-Based Approach to Constructing a Domain Sentiment Lexicon: a Case Study in Financial Distress Prediction-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A Deep Learning-Based Approach to Constructing a Domain Sentiment Lexicon: a Case Study in Financial Distress Prediction

Published:2021-09 Issue:5 Volume:58 Page:102673
ISSN:0306-4573
Container-title:Information Processing & Management
language:en
Short-container-title:Information Processing & Management

Author:

Li Shixuan,Shi Wenxuan,Wang Jiancheng,Zhou Heshen

Funder

Wuhan University of Technology

Major Program of National Fund of Philosophy and Social Science of China

Publisher

Elsevier BV

Subject

Library and Information Sciences,Management Science and Operations Research,Computer Science Applications,Media Technology,Information Systems

Reference56 articles.

1. Sentiwordnet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining;Baccianella;Lrec,2010

2. Financial report readability and stock return synchronicity;Bai;Applied Economics,2019

3. A New Chinese Financial Sentiment Dictionary for Textual Analysis in Accounting and Finance;Bian,2019

4. On the Construction and Analysis of Chinese Financial Sentiment Lexicon for Financial News;Chang,2015

5. Deep learning for sentiment analysis on google play consumer review;Day;IEEE,2017

Cited by 63 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Financial distress prediction with annual reports-based deep textual feature extraction: A hybrid approach;Information Sciences;2025-01

2. Forecasting time to risk based on multi-party data: An explainable privacy-preserving decentralized survival analysis method;Information Processing & Management;2025-01

3. A two-stage case-based reasoning driven classification paradigm for financial distress prediction with missing and imbalanced data;Expert Systems with Applications;2024-09

4. Corporate financial distress prediction using the risk-related information content of annual reports;Information Processing & Management;2024-09

5. Predicting financial distress using multimodal data: An attentive and regularized deep learning method;Information Processing & Management;2024-07

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3