Earticle

초록

영어

In view of the fact that the propagation path topology cannot effectively deal with complex social network consists of hundreds of millions of users. More researchers choose to use machine learning methods to complete retweet prediction. Those use the classification method to judge whether a message will be retweeted or not. This paper argues that retweet prediction should be regression analysis problem, not just the classification problem. Through collecting user characteristics on Twitter and selecting some features which have an important impact on the retweet behavior, a Prediction algorithm Based on the Logistic Regression for users Retweet Times in social network was proposed. Experiment results based on the actual data set show the regression analysis predicting model has a good predicting accuracy in dealing with retweet predicting, the proposed method is effectiveness.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Retweet Predicting based on Regression Analysis
 4. Experiments
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Haihao Yu [ Heilongjiang Institute of Technology, Harbin, China ]
• Xu Feng Bai [ Heilongjiang Institute of Technology, Harbin, China ]
• ChengZhe Huang [ Heilongjiang Institute of Technology, Harbin, China ]
• Haoliang Qi [ Heilongjiang Institute of Technology, Harbin, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605