Correlate influential news article events to stock quote movement

Arun Chaitanya Mandalapu; Saranya Gunabalan; Avinash Sadineni; Taotao Cai; Nur Al Hasan Haldar; Jianxin Li

doi:10.1007/978-3-030-35231-8_24

Correlate influential news article events to stock quote movement

Arun Chaitanya Mandalapu, Saranya Gunabalan, Avinash Sadineni, Taotao Cai^*, Nur Al Hasan Haldar^*, Jianxin Li

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

3 Citations (Scopus)

Abstract

This 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.

Original language	English
Title of host publication	Advanced Data Mining and Applications - 15th International Conference, ADMA 2019, Proceedings
Editors	Jianxin Li, Sen Wang, Shaowen Qin, Xue Li, Shuliang Wang
Place of Publication	Cham, Switzerland
Publisher	Springer, Springer Nature
Pages	331-342
Number of pages	12
ISBN (Electronic)	9783030352318
ISBN (Print)	9783030352301
DOIs	https://doi.org/10.1007/978-3-030-35231-8_24
Publication status	Published - 2019
Externally published	Yes
Event	15th International Conference on Advanced Data Mining and Applications, ADMA 2019 - Dalian, China Duration: 21 Nov 2019 → 23 Nov 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11888 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th International Conference on Advanced Data Mining and Applications, ADMA 2019
Country/Territory	China
City	Dalian
Period	21/11/19 → 23/11/19

Keywords

Correlation
Name entity recognition
Sentiment analysis

Access to Document

10.1007/978-3-030-35231-8_24

Cite this

Mandalapu, A. C., Gunabalan, S., Sadineni, A., Cai, T., Hasan Haldar, N. A., & Li, J. (2019). Correlate influential news article events to stock quote movement. In J. Li, S. Wang, S. Qin, X. Li, & S. Wang (Eds.), Advanced Data Mining and Applications - 15th International Conference, ADMA 2019, Proceedings (pp. 331-342). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11888 LNAI). Springer, Springer Nature. https://doi.org/10.1007/978-3-030-35231-8_24

Mandalapu, Arun Chaitanya ; Gunabalan, Saranya ; Sadineni, Avinash et al. / Correlate influential news article events to stock quote movement. Advanced Data Mining and Applications - 15th International Conference, ADMA 2019, Proceedings. editor / Jianxin Li ; Sen Wang ; Shaowen Qin ; Xue Li ; Shuliang Wang. Cham, Switzerland : Springer, Springer Nature, 2019. pp. 331-342 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "This 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.",

keywords = "Correlation, Name entity recognition, Sentiment analysis",

author = "Mandalapu, {Arun Chaitanya} and Saranya Gunabalan and Avinash Sadineni and Taotao Cai and {Hasan Haldar}, {Nur Al} and Jianxin Li",

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Mandalapu, AC, Gunabalan, S, Sadineni, A, Cai, T, Hasan Haldar, NA & Li, J 2019, Correlate influential news article events to stock quote movement. in J Li, S Wang, S Qin, X Li & S Wang (eds), Advanced Data Mining and Applications - 15th International Conference, ADMA 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11888 LNAI, Springer, Springer Nature, Cham, Switzerland, pp. 331-342, 15th International Conference on Advanced Data Mining and Applications, ADMA 2019, Dalian, China, 21/11/19. https://doi.org/10.1007/978-3-030-35231-8_24

Correlate influential news article events to stock quote movement. / Mandalapu, Arun Chaitanya; Gunabalan, Saranya; Sadineni, Avinash et al.
Advanced Data Mining and Applications - 15th International Conference, ADMA 2019, Proceedings. ed. / Jianxin Li; Sen Wang; Shaowen Qin; Xue Li; Shuliang Wang. Cham, Switzerland: Springer, Springer Nature, 2019. p. 331-342 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11888 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Correlate influential news article events to stock quote movement

AU - Mandalapu, Arun Chaitanya

AU - Gunabalan, Saranya

AU - Sadineni, Avinash

AU - Cai, Taotao

AU - Hasan Haldar, Nur Al

AU - Li, Jianxin

PY - 2019

Y1 - 2019

N2 - This 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.

AB - This 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.

KW - Correlation

KW - Name entity recognition

KW - Sentiment analysis

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SN - 9783030352301

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Advanced Data Mining and Applications - 15th International Conference, ADMA 2019, Proceedings

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A2 - Wang, Sen

A2 - Qin, Shaowen

A2 - Li, Xue

A2 - Wang, Shuliang

PB - Springer, Springer Nature

CY - Cham, Switzerland

T2 - 15th International Conference on Advanced Data Mining and Applications, ADMA 2019

Y2 - 21 November 2019 through 23 November 2019

ER -

Mandalapu AC, Gunabalan S, Sadineni A, Cai T, Hasan Haldar NA, Li J. Correlate influential news article events to stock quote movement. In Li J, Wang S, Qin S, Li X, Wang S, editors, Advanced Data Mining and Applications - 15th International Conference, ADMA 2019, Proceedings. Cham, Switzerland: Springer, Springer Nature. 2019. p. 331-342. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-35231-8_24

Correlate influential news article events to stock quote movement

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Keywords

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