Paper Info
Title
A Proposed Framework for Evaluating the Effectiveness of Financial News Sentiment Scoring Datasets.
Abstract
The impact of financial news on financial markets has been studied extensively. A number of news sentiment scoring techniques are being widely used in research and industry. However, results from sentiment studies are hard to interpret contextual and sentiment related parameters change. Sometimes, the conditions which lead to the results are not fully documented and the results are not repeatable. Based on service-oriented computing principles, this paper proposes a framework that automates the process of incorporating different contextual parameters when running news sentiment impact studies. The framework also preserves the set of parameters/dataset and conditions for the end user to enable them to reproduce their results. This is demonstrated using a case study that shows how end users can flexibly select different contextual and sentiment related parameters and conduct news impact studies on daily stock prices.
Year
DOI
Venue
2014
10.1007/978-3-319-28151-3_3
Lecture Notes in Business Information Processing
Keywords
Field
DocType
Sentiment analysis,Financial news,Stock returns,News analytics,Event studies,ADAGE,TRNA
Data science,Actuarial science,Financial news,End user,Sentiment analysis,Computer science,News analytics,Adage,Impact studies,Financial market,Event study
Conference
Volume
ISSN
Citations 
217
1865-1348
0
PageRank 
References 
Authors
0.34
12
3
Name
Order
Citations
PageRank
Islam Qudah100.68
Fethi Rabhi242750.68
Maurice Peat322.74