Correlate Influential News Article Events to Stock Quote Movement

Paper


Mandalapu, Arun Chaitanya, Gunabalan, Saranya, Sadineni, Avinash, Cai, Taotao, Hasan, Nur Al Hasan and Li, Jianxin. 2019. "Correlate Influential News Article Events to Stock Quote Movement ." Li, Jianxin, Wang, Sen, Qin, Shaowen, Li, Xue and Wang, Shuliang (ed.) 15th International Conference on Advanced Data Mining and Applications. Dalian, China 21 - 23 Nov 2019 Switzerland. Springer. https://doi.org/10.1007/978-3-030-35231-8_24
Paper/Presentation Title

Correlate Influential News Article Events to Stock Quote Movement

Presentation TypePaper
AuthorsMandalapu, Arun Chaitanya, Gunabalan, Saranya, Sadineni, Avinash, Cai, Taotao, Hasan, Nur Al Hasan and Li, Jianxin
EditorsLi, Jianxin, Wang, Sen, Qin, Shaowen, Li, Xue and Wang, Shuliang
Journal or Proceedings TitleProceedings of 15th International Conference on Advanced Data Mining and Applications (ADMA 2019)
Journal Citation11888, pp. 331-342
Number of Pages12
Year2019
PublisherSpringer
Place of PublicationSwitzerland
ISBN9783030352318
9783030352301
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-030-35231-8_24
Web Address (URL) of Paperhttps://link.springer.com/chapter/10.1007/978-3-030-35231-8_24
Web Address (URL) of Conference Proceedingshttps://link.springer.com/book/10.1007/978-3-030-35231-8
Conference/Event15th International Conference on Advanced Data Mining and Applications
Event Details
15th International Conference on Advanced Data Mining and Applications
Parent
International Conference on Advanced Data Mining and Applications
Delivery
In person
Event Date
21 to end of 23 Nov 2019
Event Location
Dalian, China
AbstractThis study is to investigate the digital media influence on financial equity stocks. For investment plans, knowledge-based decision support system is an important criterion. The stock exchange is becoming one of the major areas of investments. Various factors affect the stock exchange in which social media and digital news articles are found to be the major factors. As the world is more connected now than a decade ago, social media does play a main role in making decisions and change the perception of looking at things. Therefore a robust model is an important need for forecasting the stock prices movement using social media news or articles. From this line of research, we assess the performance of correlation-based models to check the rigorousness over the large data sets of stocks and the news articles. We evaluate the various stock quotes of entities across the world on the day news article is published. Conventional sentiment analysis is applied to the news article events to extract the polarity by categorizing the positive and negative statements to study their influence on the stocks based on correlation.
KeywordsCorrelation; Sentiment analysis; Name entity recognition
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 20204602. Artificial intelligence
Public NotesFiles associated with this item cannot be displayed due to copyright restrictions.
SeriesLecture Notes in Computer Science
Byline AffiliationsDeakin University
School of Mathematics, Physics and Computing
University of Western Australia
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