Research on Stock Prediction in China based on Social Network and SVM Algorithm
- DOI
- 10.2991/icedem-18.2018.108How to use a DOI?
- Keywords
- Social Network; Stock Prediction; Support Vector Machine (SVM); Regression
- Abstract
To some extent, the information from social network can have an impact on the investment decisions of people. Based on behavioral finance theory, this thesis focuses on the influence of social networks on the stock market and forecast the stock price. Firstly, it collects data from the social network platform, and explores the relationship between social network information and stock trading volume and stock fluctuations. Secondly by means of SVM algorithm, then a stock price forecasting model is established to predict the stock price, which verifies that there is a positive correlation between stock market and social network information. Finally, the experimental results prove that the accuracy of SVM algorithm is high.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Li Tang AU - Shuhua Zhang AU - Li He AU - Huiyu Fan PY - 2018/12 DA - 2018/12 TI - Research on Stock Prediction in China based on Social Network and SVM Algorithm BT - Proceedings of the 2018 2nd International Conference on Economic Development and Education Management (ICEDEM 2018) PB - Atlantis Press SP - 435 EP - 438 SN - 2352-5398 UR - https://doi.org/10.2991/icedem-18.2018.108 DO - 10.2991/icedem-18.2018.108 ID - Tang2018/12 ER -