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Financial sentiment classification with fresh and hot public opinions

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成果类型:
期刊论文
作者:
Cao, Shiyang;Ma, Xiao;Zeng, Jiangfeng;Yi, Ming
通讯作者:
Zeng, JF
作者机构:
[Cao, Shiyang] Shanxi Univ Finance & Econ, Int Exchange & Cooperat Dept, Taiyuan, Peoples R China.
[Ma, Xiao] Zhongnan Univ Econ & Law, Sch Informat & Safety Engn, Wuhan, Peoples R China.
[Yi, Ming; Zeng, Jiangfeng] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.
[Zeng, Jiangfeng] Ctr Data Governance & Intelligent Decis Making Hub, Wuhan, Peoples R China.
通讯机构:
[Zeng, JF ] C
Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.
Ctr Data Governance & Intelligent Decis Making Hub, Wuhan, Peoples R China.
语种:
英文
关键词:
Financial sentiment analysis;Fresh and hot opinions;Temporal modeling;Fresh-hot bilinear pooling
期刊:
Computers & Electrical Engineering
ISSN:
0045-7906
年:
2023
卷:
111
页码:
108955
基金类别:
National Natural Science Foundation of China [62102159]; Humanities and Social Science Fund of Ministry of Education of China [21YJC870002]; Natural Science Foundation of Hubei Province, China [2023AFB1018]; Fundamental Research Funds for the Central Universities, China [CCNU22QN017]; Knowledge Innovation Program of Wuhan-Shuguang Project [2022010801020287]
机构署名:
本校为通讯机构
院系归属:
信息管理学院
摘要:
Financial sentiment analysis aims to extract public opinion about an institution to help financial researchers make better decisions. To predict sentiment more accurately, it is necessary for models to improve their capability to capture long-term temporal information and support multi-user interaction. However, existing methods only analyze sentiment based on one comment from a user, which fails to fully exploit the latent emotions of the public, and they lack effective temporal modeling and interaction capabilities. In this paper, we analyze a company from two perspectives to alleviate the a...

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