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  5. Textual sentiment in finance: A survey of methods and models
 
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Textual sentiment in finance: A survey of methods and models

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Author(s)
Kearney, Colm 
Liu, Sha 
Uri
http://hdl.handle.net/10197/8213
Date Issued
May 2014
Date Available
12T13:11:16Z December 2016
Abstract
We survey the textual sentiment literature, comparing and contrasting the various information sources, content analysis methods, and empirical models that have been used to date. We summarize the important and influential findings about how textual sentiment impacts on individual, firm-level and market-level behavior and performance, and vice versa. We point to what is agreed and what remains controversial. Promising directions for future research are emerging from the availability of more accurate and efficient sentiment measures resulting from increasingly sophisticated textual content analysis coupled with more extensive field-specific dictionaries. This is enabling more wide-ranging studies that use increasingly sophisticated models to help us better understand behavioral finance patterns across individuals, institutions and markets.
Type of Material
Journal Article
Publisher
Elsevier
Journal
International Review of Financial Analysis
Volume
33
Start Page
171
End Page
185
Copyright (Published Version)
2014 Elsevier
Keywords
  • Behavioral finance

  • Textual sentiment

  • Internet messages

  • News

  • Market efficiency

Classification
D80
D82
G02
G10
G12
G14
G30
G34
G38
M41
DOI
10.1016/j.irfa.2014.02.006
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Business Research Collection
Scopus© citations
267
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Jun 1, 2023
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