Incorporation of company-related factual knowledge into pre-trained language models for stock-related spam tweet filtering-Reference-Cited by-同舟云学术

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Incorporation of company-related factual knowledge into pre-trained language models for stock-related spam tweet filtering

Published:2023-12 Issue: Volume:234 Page:121021
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Park Jihye^ORCID,Cho Sungzoon^ORCID

Funder

National Research Foundation of Korea

Ministry of Science, ICT and Future Planning

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference56 articles.

1. Finbert: Financial sentiment analysis with pre-trained language models;Araci,2019

2. Semi-supervised text mining for monitoring the news about the ESG performance of companies;Borms,2021

3. Anatomy of a stablecoin’s failure: The terra-luna case;Briola;Finance Research Letters,2022

4. Sentiment analysis in financial texts;Chan;Decision Support Systems,2017

5. Mining opinion holders and opinion patterns in US financial statements;Chen,2011

Cited by 4 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. Enhancing Financial Sentiment Analysis Ability of Language Model via Targeted Numerical Change-Related Masking;IEEE Access;2024

2. Semantic Analysis Using Deep Learning for Predicting Stock Trends;Procedia Computer Science;2024

3. esCorpius-m: A Massive Multilingual Crawling Corpus with a Focus on Spanish;Applied Sciences;2023-11-08

4. Estimating the Personality of White-Box Language Models;2023

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