Correlate Influential News Article Events to Stock Quote Movement

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

Research output: Chapter in Book/Conference paperConference paperpeer-review

1 Citation (Scopus)


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 languageEnglish
Title of host publicationAdvanced Data Mining and Applications
Subtitle of host publication15th International Conference, ADMA 2019, Proceedings
EditorsJianxin Li, Sen Wang, Shaowen Qin, Xue Li, Shuliang Wang
Place of PublicationChina
Number of pages12
ISBN (Print)9783030352301
Publication statusPublished - 23 Nov 2019
Event15th International Conference on Advanced Data Mining and Applications, ADMA 2019 - Dalian, China
Duration: 21 Nov 201923 Nov 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11888 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th International Conference on Advanced Data Mining and Applications, ADMA 2019
Internet address


Dive into the research topics of 'Correlate Influential News Article Events to Stock Quote Movement'. Together they form a unique fingerprint.

Cite this