Predicting Stock Movement using Sentiment Analysis of Twitter Feed

被引：0

作者：

Chakraborty, Pranjal ^{[1
]}

Pria, Ummay Sani ^{[1
]}

Rony, Md Rashad Al Hasan ^{[1
]}

Majumdar, Mahbub Alam ^{[1
]}

机构：

[1] BRAC Univ, Dept Comp Sci & Engn, 66 Mohakhali, Dhaka, Bangladesh

来源：

2017 6TH INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS AND VISION & 2017 7TH INTERNATIONAL SYMPOSIUM IN COMPUTATIONAL MEDICAL AND HEALTH TECHNOLOGY (ICIEV-ISCMHT) | 2017年

关键词：

Tweets; Sentiment analysis; Decision tree; Opinion mining; Machine Learning; Random forest; Boosted tree; Support Vector Machine (SVM);

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Collecting data from social networking sites is a popular way of opinion mining. These opinions show the sentimental state of a large number of people. In this paper, we have shown how much we can predict stock movement from twitter's tweets sentiment analysis. Our work is done on one year's (2016) data of tweets that contained 'stock market', 'stocktwits', 'AAPL' keywords. `AAPL' related tweets were used to see if these tweets can predict the company's stock indices whereas 'stock market', 'stocktwits' related tweets for predicting the stock market movement of US. Since we are predicting the stock values, we used Boosted Regression Tree model for this purpose.

引用

页数：6

共 16 条

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